Collapsing of multiple nested loops, methods and instructions

ABSTRACT

In an embodiment, the present invention is directed to a processor including a decode logic to receive a multi-dimensional loop counter update instruction and to decode the multi-dimensional loop counter update instruction into at least one decoded instruction, and an execution logic to execute the at least one decoded instruction to update at least one loop counter value of a first operand associated with the multi-dimensional loop counter update instruction by a first amount. Methods to collapse loops using such instructions are also disclosed. Other embodiments are described and claimed.

TECHNICAL FIELD

The present disclosure relates generally to computing platforms and moreparticularly, to loop collapsing methods, apparatus and instructions.

BACKGROUND

Nested loops, e.g., of two to five times, are very common in highperformance computing (HPC) code, for instance. Loop collapsing improvesperformance by reducing the number of branches and hence the probabilityof branch mispredictions. A conventional way to collapse multi-nestedloops is to create a loop without nests, controlled by a new loopcounter that is incremented on every iteration of the collapsed loop.The new loop counter is incremented (tc_(n-1)*tc_(n-2)* . . . *tc₀)times totally, where tc_(j) is a loop count of the loop over i_(j).However, the information about individual loop counters needs to bepreserved for computations inside the loop and for use as indexes toaccess multi-dimensional arrays.

Also, while loop collapsing in some cases may improve performance,current compilers rarely can efficiently collapse loops. A few mostfrequently seen reasons that prevent collapsing include: non-stridememory accesses in n-dimensional array A (after collapsing); existenceof accesses to a sub-dimensional array B (m-dimensions, m<n); andexistence of computations over separate loop counters (i_(j)).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a processor pipeline in accordance with anembodiment of the present invention.

FIGS. 2A and 2B are block diagrams of compare scalar vs. vectoroperations in accordance with an embodiment of the present invention.

FIG. 3A is a block diagram of a multi-dimensional loop counter vectorand an associated mask in accordance with one embodiment of the presentinvention.

FIG. 3B is a block diagram of values associated with a loop counterupdate instruction in accordance with an embodiment of the presentinvention.

FIG. 4 is a flow diagram of a method in accordance with an embodiment ofthe present invention.

FIG. 5 is a block diagram of a portion of a vector execution unit inaccordance with an embodiment of the present invention.

FIG. 6A is an illustration of an exemplary AVX instruction format inaccordance with an embodiment of the present invention.

FIG. 6B is an illustration in which fields from FIG. 6A make up a fullopcode field and a base operation field in accordance with an embodimentof the present invention.

FIG. 6C is an illustration in which fields from FIG. 6A make up aregister index field in accordance with an embodiment of the presentinvention.

FIGS. 7A and 7B are block diagrams illustrating a generic vectorfriendly instruction format and instruction templates thereof accordingto embodiments of the invention.

FIG. 8A is a block diagram illustrating an exemplary specific vectorfriendly instruction format according to embodiments of the invention.

FIG. 8B is a block diagram illustrating the fields of the specificvector friendly instruction format in accordance with one embodiment ofthe invention.

FIG. 8C is a block diagram illustrating the fields of the specificvector friendly instruction format in accordance with one embodiment ofthe invention.

FIG. 8D is a block diagram illustrating the fields of the specificvector friendly instruction format according to embodiments of theinvention.

FIG. 9 is a block diagram of a register architecture according to oneembodiment of the invention.

FIG. 10A is a block diagram illustrating both an exemplary in-orderpipeline and an exemplary register renaming, out-of-orderissue/execution pipeline according to embodiments of the invention.

FIG. 10B is a block diagram illustrating both an exemplary embodiment ofan in-order architecture core and an exemplary register renaming,out-of-order issue/execution architecture core to be included in aprocessor according to embodiments of the invention.

FIGS. 11A-B illustrate a block diagram of a more specific exemplaryin-order core architecture, which core would be one of several logicblocks (including other cores of the same type and/or different types)in a chip.

FIG. 12 is a block diagram of a processor that may have more than onecore, may have an integrated memory controller, and may have integratedgraphics according to embodiments of the invention.

FIG. 13 is a block diagram of an exemplary system in accordance with anembodiment of the present invention.

FIG. 14 is a block diagram of a first more specific exemplary system inaccordance with an embodiment of the present invention.

FIG. 15 is a block diagram of a second more specific exemplary system inaccordance with an embodiment of the present invention.

FIG. 16 is a block diagram of a SoC in accordance with an embodiment ofthe present invention.

FIG. 17 is a block diagram contrasting the use of a software instructionconverter to convert binary instructions in a source instruction set tobinary instructions in a target instruction set according to embodimentsof the invention.

DETAILED DESCRIPTION

In various embodiments, loop counters for nested loops may be maintainedin a vector format. These multiple loop counters can be modifiedaccordingly at the end of each iteration of a collapsed loop formed ofthe nested loops. In different embodiments, post-computational loopcounter updates may be performed in hardware of a processor responsiveto a single instruction.

Embodiments thus may store loop counters of nested loops as a singlemulti-dimensional loop counter stored in a vector-sized storage such asa vector register of a processor or a vector-sized memory location. Thevalue in this storage may be controlled via one or more instructions forcontrolling the multi-dimensional loop counter. Different flavors ofsuch instructions may be provided for incrementing and decrementing thecounters in a controllable manner, as well as updating various statusflags of a processor. In addition, an instruction that calculatesoffsets inside multi-dimensional arrays may be used to perform loopcollapsing. This approach makes it possible to collapse multi-nestedloops and using loop counters of nested loops as indexes for accesses tomulti-dimensional arrays (including sub-dimensional arrays) or othercomputations over loop counters of nested loops.

FIG. 1 shows a high level diagram of a processing core 100 implementedwith logic circuitry on a semiconductor chip. The processing coreincludes a pipeline 101. The pipeline consists of multiple stages eachdesigned to perform a specific step in the multi-step process needed tofully execute a program code instruction. These typically include atleast: 1) instruction fetch and decode; 2) data fetch; 3) execution; 4)write-back. The execution stage performs a specific operation identifiedby an instruction that was fetched and decoded in prior stage(s) (e.g.,in step 1) above) upon data identified by the same instruction andfetched in another prior stage (e.g., step 2) above). The data that isoperated upon is typically fetched from (general purpose) registerstorage space 102. New data that is created at the completion of theoperation is also typically “written back” to register storage space(e.g., at stage 4) above).

The logic circuitry associated with the execution stage is typicallycomposed of multiple “execution units” or “functional units” 103_1 to103_N that are each designed to perform its own unique subset ofoperations (e.g., a first functional unit performs integer mathoperations, a second functional unit performs floating pointinstructions, a third functional unit performs load/store operationsfrom/to cache/memory, etc.). The collection of all operations performedby all the functional units corresponds to the “instruction set”supported by the processing core 100.

Two types of processor architectures are widely recognized in the fieldof computer science: “scalar” and “vector”. A scalar processor isdesigned to execute instructions that perform operations on a single setof data, whereas, a vector processor is designed to execute instructionsthat perform operations on multiple sets of data. FIGS. 2A and 2Bpresent a comparative example that demonstrates the basic differencebetween a scalar processor and a vector processor.

FIG. 2A shows an example of a scalar AND instruction in which a singleoperand set, A and B, are ANDed together to produce a singular (or“scalar”) result C (i.e., AB=C). By contrast, FIG. 2B shows an exampleof a vector AND instruction in which two operand sets, A/B and D/E, arerespectively ANDed together in parallel to simultaneously produce avector result C, F (i.e., A.AND.B=C and D.AND.E=F). As a matter ofterminology, a “vector” is a data element having multiple “elements”.For example, a vector V=Q, R, S, T, U has five different elements: Q, R,S, T and U. The “size” of the exemplary vector V is five (because it hasfive elements).

FIG. 1 also shows the presence of vector register space 107 that isdifferent than general purpose register space 102. Specifically, generalpurpose register space 102 is nominally used to store scalar values. Assuch, when, any of execution units perform scalar operations theynominally use operands called from (and write results back to) generalpurpose register storage space 102. By contrast, when any of theexecution units perform vector operations they nominally use operandscalled from (and write results back to) vector register space 107.Different regions of memory may likewise be allocated for the storage ofscalar values and vector values.

Note also the presence of masking logic 104_1 to 104_N and 105_1 to105_N at the respective inputs to and outputs from the functional units103_1 to 103_N. In various implementations, for vector operations, onlyone of these layers is actually implemented—although that is not astrict requirement (although not depicted in FIG. 1, conceivably,execution units that only perform scalar and not vector operations neednot have any masking layer). For any vector instruction that employsmasking, input masking logic 104_1 to 104_N and/or output masking logic105_1 to 105_N may be used to control which elements are effectivelyoperated on for the vector instruction. Here, a mask vector is read froma mask register space 106 (e.g., along with input operand vectors readfrom vector register storage space 107) and is presented to at least oneof the masking logic 104, 105 layers.

Over the course of executing vector program code each vector instructionneed not require a full data word. For example, the input vectors forsome instructions may only be 8 elements, the input vectors for otherinstructions may be 16 elements, the input vectors for otherinstructions may be 32 elements, etc. Masking layers 104/105 aretherefore used to identify a set of elements of a full vector data wordthat apply for a particular instruction so as to effect different vectorsizes across instructions. Typically, for each vector instruction, aspecific mask pattern kept in mask register space 106 is called out bythe instruction, fetched from mask register space and provided to eitheror both of the mask layers 104/105 to “enable” the correct set ofelements for the particular vector operation.

Vector machines can be designed to process “multi-dimensional” datastructures, where, each element of the vector corresponds to a uniquedimension of the data structure. For example, if a vector machine wereto be programmed to contemplate a three dimensional structure (such as a“cube”), a vector might be created having a first element thatcorresponds to the cube's width, a second element that corresponds tothe cube's length and a third element that corresponds to the cube'sheight.

Those of ordinary skill will understand that computation ofmulti-dimensional structures in a computing system can entail structureshaving two or more dimensions including more than three dimensions. Forsimplicity, however, the present application will mostly provideexamples.

Table 1 is an example nested loop that can be collapsed usinginstructions described herein. Note that the loop collapsing may beperformed by a user or a compiler such as a static compiler or a runtimecompiler such as a just in time (JIT) compiler. In general, Table 1shows a nested loop in which updates are made to a firstmulti-dimensional array A based on computations performed on loopcounters of nested loops (i_(j)) and on data elements obtained from asecond multi-dimensional array B, based on offsets according to variousloop counter values.

TABLE 1 for(i_(n−1)=istart_(n−1); i_(n−1)<= iend_(n−1); i_(n−1)+=str_(n−1))  for(i_(n−2)=istart_(n−2); i_(n−2)<= iend_(n−2); i_(n−2)+=str_(n−2))   ...   for(i₀=istart₀; i₀<= iend₀; i₀+= str₀){   A[i_(n−1)][i_(n−2)]...[i₁][i₀] =Computation((i_(n−1),i_(n−2),...,i₀),   B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)])    }

Referring now to FIG. 3A, shown is a block diagram of amulti-dimensional loop counter vector MDLC that includes a plurality ofoffsets. Note that as here when KL is greater than n, values at offsetsgreater than or equal to n are undefined, and can be masked out fromcomputations by a mask k1.

In some embodiments these instructions to update a multi-dimensionalloop counter modify values of the multi-dimensional loop counter inorder to cross to the next iteration of the collapsed loop. There areseveral implementations, but all of them are intended to do onething—cross to the next iteration of collapsed loop or, in terms of thecollapsed loop, perform an increment operation.

Referring now to FIG. 3B, shown are values associated with a loopcounter update instruction in accordance with an embodiment of thepresent invention. As shown in FIG. 3B, various operands and mask valuesare present. Note that while in particular examples these values may beidentified in an instruction as operands or a mask value, in otherimplementations an immediate value also may be associated with aninstruction to identify one or more values for use in execution of theinstruction.

As seen in FIG. 3B, a first operand identifies a first storage location110 (e.g., a vector register ZMM0) which in an embodiment may be anKL-wide register to store KL individual data elements. Although thescope of the present invention is not limited in this regard indifferent implementations KL may be 8,16, 32, or another number ofindividual data elements. For example, if a vector register is 512 bitswide and each loop counter size is 32 bits, then KL=512/32=16. Note thatelements at an offset of zero, e.g., zmm[0], are related to an innermostloop, a next offset, e.g., zmm[1], corresponds to a one time outer loop,and finally zmm[n] corresponds to the outermost loop. In an exampleinstruction such as a loop counter update instruction, this register maystore the current values for each of the individual loop counters of themulti-dimensional loop counter vector.

In turn, a second operand identifies a second storage location 120(e.g., a vector register ZMM1) which in an embodiment may be an KL-wideregister to store KL individual data elements. In an example loopcounter update instruction, this register may store the start values foreach of the individual loop counters of the multi-dimensional loopcounter vector.

In turn, a third operand identifies a second storage location 130 (e.g.,a vector register ZMM2) which in an embodiment may be an KL-wideregister to store KL individual data elements. In an example loopcounter update instruction, this register may store the end values foreach of the individual loop counters of the multi-dimensional loopcounter vector.

Finally, FIG. 3B shows an additional storage location 140 such asanother vector register that stores a mask k1 including a plurality ofelements each used to identify whether a particular loop counter valueof the loop counter vector is to be masked during execution of the loopcounter update instruction. A mask also may be used when the number ofelements that fit into a vector register (KL) is larger than the numberof nested loops (n). In this case upper elements of operands startingfrom offset n may be masked out from computations. Hereafter, it will beassumed that number of loop nests (n) is not more than the number ofelements in a vector (KL), and when n<KL it will be assumed that upperelements, starting from offset n, are masked out from multi-dimensionalloop counter update computations by an appropriate input mask k1.

Referring now to FIG. 4, shown is a flow diagram of a method inaccordance with an embodiment of the present invention. Morespecifically, FIG. 4 shows a method for executing a loop counter updateinstruction as described herein. In an embodiment, method 300 may beperformed by various execution logic of a vector processor such as oneor more logic units within a vector execution unit and/or a scalarexecution unit of a processor core of a multicore processor. In theembodiment of FIG. 4, method 300 begins by receiving a decodedinstruction and operands associated with the instruction (block 305).Optionally, a mask and/or one or more immediate values associated withthe instruction also may be received. Next control passes to diamond 310to determine whether a particular element of a mask vector indicatesthat the mask is active for this element.

If not, control passes to block 360 where increment of an element counthappens. If all elements of the loop counter vector have been processed(determined at diamond 370), then execution comes to block 340, wherethe update operation may conclude, indicating a crossing to a nextiteration of the collapsed loop or completion of the collapsed loop.Otherwise, execution returns back to diamond 310.

If the answer at diamond 310 is yes, control passes to diamond 320 whereit can be determined whether a current loop counter value element of aloop counter vector is less than the corresponding end value element ofan end value vector. In other words, it is determined whether the loopcounter value is not the last one from the scope of possible values in arelated nested loop. If it is not the last value, execution comes toblock 330, where the current loop counter value element is updated toits value on the next iteration of the related nested loop. In anembodiment in which the loop counter update instruction is an incrementinstruction, this update may be by incrementing the value, e.g., by 1according to one flavor of the instruction or by a configurable amountaccording to a different flavor of the instruction. Control next passesto block 340 where the update operation may conclude, indicating acrossing to a next iteration of the collapsed loop. In an embodiment, abranch operation may occur to thus pass control to a target location.

Still referring to FIG. 4, if instead at diamond 320 it is determinedthat the given loop counter cannot be updated to the value of the nextiteration of related nested loop, control passes to block 350 where thecurrent loop counter value element is updated to a corresponding startvalue element of a start value vector. Note that if all loop countervalues are set to their start value and no update of any loop counter toa value on a next iteration of a related nested loop happened (incrementoperation), then the collapsed loop, of which this instruction is apart, is completed. From block 350 control passes to block 360 where anelement count for this update operation can be incremented andaccordingly, the method may proceed through the next nested loop.Although shown at this high level in the embodiment of FIG. 4,understand the scope of the present invention is not limited in thisregard.

Referring now to FIG. 5, shown is a block diagram of a portion of avector execution unit in accordance with an embodiment of the presentinvention. As shown in FIG. 5, vector execution unit 400 includesvarious logic elements to perform operations on data to thus achieve adesired result. In the implementation shown in FIG. 5, a mask detectionlogic 410 is coupled to receive incoming values associated with aninstruction. In the context of a loop counter update instruction thesevalues may be as described above, namely current values of the loopcounters, start and end values for the loop counters and a mask, in oneimplementation. Mask detection logic 410 thus may determine, for eachelement of the vector, whether an operation is to be performed or thegiven element should be masked. If an operation is to be performed, acomparison logic 420 may perform a comparison between a current value ofa loop counter element and a given one of a start or end value (forexample).

Still referring to FIG. 5, a loop counter/control update logic 430 may,based on a result of the comparison, update a loop counter valueelement, e.g., by increment or decrement. Still further, one or morecontrol values also may be updated. Finally, a branch logic 440 maycause a branch operation to occur once an update to a loop counter valueelement has occurred. Of course understand that a vector execution unitmay include greater amounts of logic to perform loop counter and othervector instructions.

In an embodiment, a user-level vector instruction can be used toincrement multi-dimensional loop counters of a collapsed multi-nestedloop. In an embodiment, this instruction is of the form: MDLCINCzmm0{k1},zmm1,zmm2. Here zmm1 is a vector of starting values of the loopcounters in each nested loop (istart_(n-1), istart_(n-2), . . . ,istart₀), zmm2 is a vector of ending values of the loop counters in eachnested loop (iend_(n-1), iend_(n-2), . . . , iend₀), zmm0 is a vector ofcurrent values of the loop counters (i_(n-1), i_(n-2), . . . , i₀) (andinto which updates are stored), and k1 is a mask, which chooses a subsetof loop counters to increment. Thus the instruction is performed onelements of the vector of current values of the loop counters having acorresponding element of mask k1 of a first value (e.g., a logic 1), anda result, e.g., no increment, an increment, or a starting value isstored into the corresponding element of zmm0.

Pseudo-code of the instruction is as follows in Table 2.

TABLE 2 MDLCINC zmm0{k1},zmm1,zmm2 //zmm1 - starting values, zmm2 -ending for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){  if(zmm0[i]<zmm2[i]) {    zmm0[i]++    inc=0    break   }else{   zmm0[i]=zmm1[i]   }  }

In general, the pseudocode of Table 2 thus operates a for loop in whichfor values of i less than the number of vector elements (correspondingto KL), a bitwise logical ANDing of an element from the mask and anincrement bit value (inc) (initially set at one) is checked. If thisbitwise-AND equals 1, a comparison of the corresponding element of theloop counter vector (corresponding to a particular current loop countervalue) is compared to the corresponding end value element. If thecurrent loop counter value is less than this end counter value, thecurrent loop counter value is incremented and this increment bit value(inc) is set to zero, which may cause further iterations of the loop tobe avoided. Alternately, as shown in Table 2 a branch operation may beperformed here to prevent further computations of loop counter values.

If instead the current loop counter value is not less than this endcounter value, the starting value for the corresponding element isstored in the current loop counter vector element.

Mask k1 can be used to control which loop counts are incremented. In anexample with 3 loop counters, i, j, k, a k1 mask of “101” can be used toonly collapse loops over i and k counters. To avoid overwriting one ofthe sources (i.e., zmm0), an implicit source can be used with theinstruction such that starting values of the loop counters areimplicitly taken from another vector register, e.g., zmm5.Alternatively, a 4-operand instruction encoding can be used thatincludes this additional operand reference.

With the loop counter increment instruction provided above, an example3-nested loop may be as follows in Table 3.

TABLE 3 ijk_start[3]={istart, jstart, kstart} // initialize valuesoutside the loop ijk_end[3]={iend, jend, kend} ijk[3]={istart, jstart,kstart} k5=111b zmm2{k5}{z}=ijk_start[2:0] // load data to the registers  zmm3{k5}{z}=ijk_end[2:0]   zmm0{k5}{z}=ijk[2:0]  i_position = 0 j_position = 1  k_position = 2 tc_of_collapsed_loop =(iend−istart+1)*(jend−jstart+1)*(kend−kstart+1) for(n=0;n<tc_of_collapsed_loop; n++){ //collapsed loop i=extract(i_position,zmm0) // extract nested loop counters from  //multi-dimensional loop counter  j=extract(j_position,zmm0) k=extract(k_position,zmm0)  computation(i,j,k,B[k][j])  // docomputations over loop   // counters, including accesses // tomulti-dimensional arrays  zmm0=mdlcinc(k5,zmm0,zmm2,zmm3) // incrementloop counters }

Note that in the above loop, the extract instruction,extract(position,zmm0), is used to return element of vector zmm0 whichstands at an offset equal to the position. So, it is simplyzmm0[position].

Embodiments thus may avoid overhead of branches inside collapsed loops.One of the purposes of loop collapsing is reducing the total number ofbranches and branch mispredicts. Using branches related to control whichloop counters are to be incremented can eliminate any performance gainfrom collapsing. Also embodiments avoid overhead of memory referencesinside the collapsed loop, as all nested loop counters are held in onevector register and can be extracted, e.g., by a single instruction(e.g., a vpcompress instruction) without referencing memory. Stillfurther, the multi-dimensional loop counter vector can be used as is byan instruction for calculating offsets inside a multi-dimensional array.This reduces overhead for accesses to multi-dimensional arrays.Embodiments also may reduce the overall number of instructions used toimplement loop collapsing.

In some cases, collapsed loops may have loop counter values that are tobe incremented differently by adding a different number to each loopcounter. An example of a nested loop with different incrementing loopcounter values is seen in Table 4.

TABLE 4 for(i_(n−1)=istart_(n−1); i_(n−1)<= iend_(n−1); i_(n−1)+=str_(n−1))  for(i_(n−2)=istart_(n−2), i_(n−2)<= iend_(n−2); i_(n−2)+=str_(n−2))   ...   for(i₀=istart₀; i₀<= iend₀; i₀+= str₀){   A[i_(n−1)][i_(n−2)]...[i₀] = Computation((i_(n−1),i_(n−2),...,i0),   B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)])    }

A 3-operand form of the above increment instruction that provides aso-called stride increment to the loop counter vector is as follows:MDLCINCSTR zmm0{k1},zmm1,zmm2. Here, zmm0 is a vector of current valuesof loop counters (i_(n-1), i_(n-2), . . . , i₀), zmm1 is a vector ofincrement factors (also referred to as stride values) in each dimension(str_(n-1), str_(n-2), . . . , str₀), zmm2 is a vector of differencesbetween ending and starting values of loop counters in each nested loop(iend_(n-1)-istart_(n-1), etc.), and k1 is a mask that chooses a subsetof loop counters to increment. Note that from these values a vector oftrip counts can be obtained as: (zmm2/zmm1+zmm_ones), where zmm_ones isa vector of ones.

Pseudo-code of this instruction is as follows in Table 5.

TABLE 5 MDLCINCSTR zmm0{k1},zmm1,zmm2 // for(i=0,inc=1; i<KL; i++)  if(k1[i] & inc){   if(zmm0[i]<=zmm2[i]−zmm1[i]) {    zmm0[i]+=zmm1[i]   inc=0    break   }else{    zmm0[i]=0   }  }

To obtain the exact values of indexes (loop counters) for furthercomputations, a vector of starting indexes may be added to the result,for example, starting indexes may be added to the resulting loop countervector as follows (zmm_start=(istart_(n-1), istart_(n-2), . . . ,istart₀)). In an embodiment, a vector add instruction may be used: VPADDzmm4,zmm_start,zmm0.

The overhead related to shifting loop counter values to zero base can beeliminated using a 4-operand form of the instruction. This instructionmay be of the form: MDLCINSCSTR zmm0{k1}, zmm1, zmm2, zmm3, wherezmm0=current values, zmm1=strides, zmm2=starting values, and zmm3=endingvalues, and k1 is a mask. This form is shown in Table 5.1:

TABLE 5.1 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){  if(zmm0[i]<=zmm3[i]−zmm1[i]) {    zmm0[i]+=zmm1[i]    inc=0    break}else{    zmm0[i]=zmm2[j]   }  }

With 3-operand encoding form provided above, an example of 3-nested loopmay be as follows in Table 6.

TABLE 6 ijk_start[3]={istart, jstart, kstart} //initialize valuesoutside the loop ijk_tc[3]={(iend−istart)/istr+1, (jend−jstart)/jstr+1,(kend−kstart)/kstr+1} //trip counts of   // loops ijk[3]={0, 0, 0}stride[3]={istr, jstr, kstr} //strides k5=111b zmm2{k5}{z}=ijk_tc[2:0]//load data to the registers zmm3{k5}{z}=ijk_start[2:0]zmm1{k5}{z}=stride[2:0] zmm0{k5}{z}=ijk[2:0] i_position = 0 j_position =1 k_position = 2 tc_of_collapsed_loop =((iend−istart)/istr+1)*((jend−jstart)/jstr+1)*((kend−kstart)/kstr+1)for(n=0; n<tc_of_collapsed_loop; n++){ //collapsed loop  zmm4 = zmm3 +zmm0 //add starting values to get correct absolute values for // i,j,k i=extract(i_position,zmm4) //extract nested loop counters frommulti-dimensional  // loop counter  j=extract(j_position,zmm4) k=extract(k_position,zmm4)  computation(i,j,k,B[k][j])  //docomputations over loop counters, including   // accesses to//multi-dimensional arrays  zmm0=mdlcincstr(k5,zmm0,zmm1,zmm2)//increment loop counters }

Collapsing of multi-nested loops also may be aided using an instructionthat decrements a multi-dimensional loop counter. An example of a nestedloop with decrementing loop counter values is seen in Table 7.

TABLE 7 for(i_(n−1)=istart_(n−1); i_(n−1)>= iend_(n−1); i_(n−1)−−) for(i_(n−2)=istart_(n−2); i_(n−2)>= iend_(n−2); i_(n−2)−−)  ...  for(i₀=istart₀; i₀>=iend₀; i₀−−){    A[i_(n−1)][i_(n−2)]...[i₀] =Computation((i_(n−1),i_(n−2),...,i₀),   B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)])   }

In an embodiment, this instruction may be of the form: MDLCDECzmm0{k1},zmm1,zmm2, where zmm1 is a vector of starting values of loopcounters (istart_(n-1), iend_(n-1), . . . , istart_(n-2), . . . ,istart₀), zmm2 is a vector of ending values of loop counters(iend_(n-1), iend_(n-2), . . . , iend₀), zmm0 is a vector of currentvalues of loop counters (i_(n-1), i_(n-2), . . . , i₀), and k1 is a maskthat chooses a subset of loop counters to decrement. The resulting zmm0vector contains values of loop counters for the next iteration of thecollapsed loop. Pseudocode of this instruction is as follows in Table 8.

TABLE 8 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){   if(zmm0[i]>zmm2[i]) {     zmm0[i]−−     inc=0     break    }else{    zmm0[i]=zmm1[i]    } }

For example, for a 3-times nested scalar loop, this decrementinstruction may be used as follows in Table 9.

TABLE 9  ijk_start[3]={istart, jstart, kstart}     //initialize valuesoutside the loop  ijk_end[3]={iend, jend, kend}  ijk[3]={istart, jstart,kstart}  k5=111b  zmm2{k5}{z}=ijk_start[2:0]  //load data to theregisters  zmm3{k5}{z}=ijk_end[2:0]  zmm0{k5}{z}=ijk[2:0]  i_position =0  j_position = 1  k_position = 2  tc_of_collapsed_loop =(istart−iend+1)*(jstart−jend+1)*  (kstart−kend+1)  for(n=0;n<tc_of_collapsed_loop; n++){ //collapsed loop  i=extract(i_position,zmm0) //extract nested loop counters frommulti-dimensional // loop counter  j=extract(j_position,zmm0) k=extract(k_position,zmm0)  computation(i,j,k,B[k][j]) //docomputations over loop counters, including  // accesses tomulti-dimensional arrays  zmm0=mdlcdec(k5,zmm0,zmm2,zmm3) //decrementloop counters }

If only a subset of the loops are to be collapsed, then a differentk-mask may be used. In the example above, collapsing loops over i and kcan be done with the same vectors zmm0, zmm1, zmm2 by binary maskk1=101.

Obtaining the value of an individual counter (if needed) can be done byvector extraction instructions, e.g., vpextr instruction. In the exampleabove, the j-counter can be extracted by the instruction: vpextr r64,zmm0,1. Here 1 is an offset of j-value inside the multidimensional loopcounter zmm0, j value will be in scalar r64 register.

In other examples, a nested loop may have counter values that aredecremented according to a variable or stride decrement values.Referring now to Table 10, shown is an example of a nested loop withdifferent decrementing loop counter values.

TABLE 10 for(i_(n−1)=istart_(n−1); i_(n−1)>= iend_(n−1); i_(n−1) −=str_(n−1))  for(i_(n−2)=istart_(n−2); i_(n−2)>= iend_(n−2); i_(n−2) −=str_(n−2))  ...   for(i₀=istart₀; i₀>= iend₀; i₀−= str₀){   A[i_(n−1)][i_(n−2)]...[i₀] = Computation((i_(n−1),i_(n−2),...,i₀),   B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)])    }

In an embodiment, a decrement stride instruction to decrement selecteddata elements by an individually controllable stride amount may be ofthe form: MDLCDECSTR zmm0{k1},zmm1,zmm2. In this case here zmm0 storesthe current loop counter values, zmm1 stores the stride value, and zmm2stores the differences between starting values and ending values(istart_(j)-iend_(j)).

Pseudocode of this instruction is as in Table 11 below.

TABLE 11 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){   if(zmm0[i]>=zmm1[i]) {     zmm0[i]−=zmm1[i]     inc=0    }else{    zmm0[i]=zmm2[i]    }  }

A 4-operand form of this instruction is as follows and shown in Table11.1.

TABLE 11.1 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){   if(zmm0[i]>=zmm2[j]+zmm1[i]) {     zmm0[i]−=zmm1[i]     inc=0    break    }else{     zmm0[i]=zmm3[i]    }  }

An example collapsed loop for a 3-nested loop using this decrementstride instruction may be as follows in Table 12.

TABLE 12  ijk_end[3]={iend, jend, kend}    //initialize values outsidethe loop  ijk_tc[3]={(istart−iend)/istr+1, (jstart−jend)/jstr+1,(kstart−kend)/kstr+1} //trip counts of   // loops  ijk[3]={istart,jstart, kstart}  stride[3]={istr, jstr, kstr}  //strides  k5=111b zmm2{k5}{z}=ijk_tc[2:0]  //load data to the registers zmm3{k5}{z}=ijk_end[2:0]  zmm1{k5}{z}=stride[2:0]  zmm0{k5}{z}=ijk[2:0] i_position = 0  j_position = 1  k_position = 2  tc_of_collapsed_loop =((istart−iend)/istr+1)*((jstart−jend)/jstr+1)*((kstart−kend)/kstr+1) for(n=0; n<tc_of_collapsed_loop; n++){  //collapsed loop   zmm4 =zmm3 + zmm0 //add ending values to get correct absolute values for   //i,j,k  i=extract(i_position,zmm4) //extract nested loop counters frommulti-dimensional  // loop counter  j=extract(j_position,zmm4) k=extract(k_position,zmm4)  computation(i,j,k,B[k][j])  //docomputations over loop counters, including   // accesses to//multi-dimensional arrays  zmm0=mdlcdecstr(k5,zmm0,zmm1,zmm2)//decrement loop counters }

More generally in some embodiments an instruction may provide forindividual increment or decrement control of loop counter values of aloop counter value vector (both of controllable factors). In this waythe different counts of a collapsed loop may be incremented ordecremented individually by adding a different number to each. Inparticular, not all loops need be incremented or decremented, andinstead some of the loops may be decremented while others areincremented. The case of all the loops incrementing or decrementing in auniform way may occur using other flavors of a multi-dimensional loopcounter control instruction, as described above.

Using such an instruction, some loops can have an increment and otherloops can have a decrement without using separate instructions to handleeach group, which would involve appropriate mask preparation to isolatethe loops that will increment and the ones that will decrement.

This generalized increment/decrement instruction may be useful insituations as in Table 13, where some loops are incremented and someloops are decremented.

TABLE 13 for(i_(n−1)=istart_(n−1); i_(n−1)<= iend_(n−1); i_(n−1)++)//some loops are incremented  for(i_(n−2)=istart_(n−2); i_(n−2)>=iend_(n−2); i_(n−2)−−) //and some are decremented  ...   for(i₀=istart₀;i₀<=iend₀; i₀++){    A[i_(n−1)][i_(n−2)]...[i₀] =Computation((i_(n−1),i_(n−2),...,i₀),   B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)])   }

In an embodiment, this generalized instruction to provide eitherincrement or decrement of selected loop counters may be of the formMDLCINCDEC zmm0{k1},zmm1,zmm2,imm, where zmm0 is the current values forthe loop counter vector, zmm1 includes starting values, zmm2 includesending values, imm is an immediate operand of n-bits (n—number of nestedloops) showing which loops are incremented (imm[i]=1) or decremented(imm[i]=0). Pseudocode for this instruction is as follows in Table 14.

TABLE 14 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){    if (imm[i]){    if(zmm0[i]<zmm2[i]) {      zmm0[i]++      inc=0      break    }else{      zmm0[i]=zmm1[i]     }    else{     if(zmm0[i]>zmm2[i]) {     zmm0[i]−−      inc=0      break     }else{      zmm0[i]=zmm1[i]    }    }  }

For the 3-nested loop of Table 15 below, this generalizedincrement/decrement instruction may be used.

TABLE 15 for(i=istart; i>=iend; i−−)  for(j=jstart; j<=jend; j++)  for(k=kstart; k<=iend; k++){     computation(i,j,k, B[j][k]);   }    Collapsed loop has again the same form: ijk_start[3]={istart,jstart, kstart} //initialize values outside the loop ijk_end[3]={iend,jend, kend} ijk[3]={istart, jstart, kstart} k5=111bzmm2{k5}{z}=ijk_start[2:0]  //load data to the registerszmm3{k5}{z}=ijk_end[2:0] zmm0{k5}{z}=ijk[2:0] imm = 110b  //i-loopcounter is decremented, j & k-loop counters are incremented i_position =0 j_position = 1 k_position = 2 tc_i_loop =(istart−iend)*(−1)*(2*imm[i_position]−1)+1 //(−1)*(2*imm[i_position]−1)is  // equal to “−1” for incremented // loops and “1” for decrementedtc_j_loop = (jstart−jend)*(−1)*(2*imm[j_position]−1)+1 //this is neededto automate // calculation of trip counts tc_k_loop =(kstart−kend)*(−1)*(2*imm[k_position]−1)+1 tc_of_collapsed_loop =tc_i_loop*tc_j_loop*tc_k_loop for(n=0; n<tc_of_collapsed_loop; n++){//collapsed loop  i=extract(i_position,zmm0) //extract nested loopcounters from multi-dimensional   //loop counter j=extract(j_position,zmm0)  k=extract(k_position,zmm0) computation(i,j,k,B[k][j])  //do computations over loop counters,including   //accesses to //multi-dimensional arrays zmm0=mdlcincdec(k5,zmm0,zmm2,zmm3,imm) //increment/decrement loopcounters }

Note that the increment/decrement control can be encoded in differentways. For example, an 8-bit immediate can be used, which will limit thenumber of loops to increment or decrement to 8. This is reasonable sinceit is rare to have more than 8 loops nested. Alternatively, a thirdoperand can encode this control, or it can be done using a mask or ageneral purpose register (GPR). It can also be encoded as an implicitsource (e.g., RAX).

Alternative implementations to avoid overwriting zmm0 (vector of currentvalues) include encoding a third source (becoming a 4 operandinstruction) or assuming an implicit source, e.g., increment countsimplicitly in ZMM5.

In other implementations, stride generalized increment/decrementinstructions may be provided such that some loops are incremented andsome loops are decremented by controllable amounts. Such situations mayoccur in the following code of Table 16.

TABLE 16 for(i_(n−1)=istart_(n−1); i_(n−1)<= iend_(n−1);i_(n−1)+=str_(n−1)) //some loops are // incremented for(i_(n−2)=istart_(n−2); i_(n−2)>= iend_(n−2); i_(n−2)−=str_(n−2)) //and some are decremented  ...   for(i₀=istart₀; i₀<= iend₀;i₀+=str₀){  A[i_(n−1)][i_(n−2)]...[i₀] =Computation((i_(n−1),i_(n−2),...,i₀), B[i_(k(m−1))][i_(k(m−2))]...[i_(k1)][i_(k0)]) }

In an embodiment, this generalized instruction to provide eitherincrementing or decrementing of a selected amount to selected dataelements may be of the form: MDLCINCDECSTR zmm0{k1},zmm1,zmm2,imm, wherezmm0 provides the current loop counter values, zmm1 are strides values,zmm2 are values of differences between end and start values, imm is animmediate operand of n-bits (n—number of nested loops) showing whichloops are incremented (imm[i]=1) or decremented (imm[i]=0). Pseudocodefor this instruction is as follows in Table 17.

TABLE 17 for(i=0,inc=1; i<KL; i++)  if (k1[i] & inc){    if (imm[i]){    if(zmm0[i]<=zmm2[i]−zmm1[i]) {      zmm0[i]+=zmm1[i]      inc=0     break     }else{      zmm0[i]=0     }    else{    if(zmm0[i]>=zmm1[i]) {      zmm0[i]−=zmm1[i]      inc=0      break    }else{      zmm0[i]=zmm2[i]     }    }  }

The following nested loop of Table 18 can be converted into collapsedform using one or more instructions in accordance with an embodiment ofthe present invention.

TABLE 18 for(i=istart; i>=iend; i−=istr)  for(j=jstart; j<=jend;j+=jstr)   for(k=kstart; k<=iend; k+=kstr){     computation(i,j,k,B[j][k]);   }     Collapsed loop has again the same form:ijk_start[3]={istart, jstart, kstart} //initialize values outside theloop ijk_end[3]={iend, jend, kend} ijk[3]={istart, jstart, kstart}k5=111b zmm2{k5}{z}=ijk_start[2:0] //load data to the registerszmm3{k5}{z}=ijk_end[2:0] zmm3 = min(zmm2,zmm3) //here we define offsetof loop counters - it is either istart  //for incremented loops or iendfor decremented ones zmm0{k5}{z}=ijk[2:0] imm = 110b  //i-loop counteris decremented, j & k-loop counters are incremented i_position = 0j_position = 1 k_position = 2 tc_i_loop =(istart−iend)*(−1)*(2*imm[i_position]−1)+1 //(−1)*(2*imm[i_position]−1)is //equal to “−1” for incremented loops and “1” //for decrementedtc_j_loop = (jstart−jend)*(−1)*(2*imm[j_position]−1)+1 //this is neededto automate   //calculation of trip counts tc_k_loop =(kstart−kend)*(−1)*(2*imm[k_position]−1)+1 tc_of_collapsed_loop =tc_i_loop*tc_j_loop*tc_k_loop for(n=0; n<tc_of_collapsed_loop;n++){ //collapsed loop  zmm4 = zmm3 + zmm0   //add offset values to getcorrect absolute values for i,j,k  i=extract(i_position,zmm4)  //extractnested loop counters from multi-dimensional //loop counter j=extract(j_position,zmm4)  k=extract(k_position,zmm4) computation(i,j,k,B[k][j])  //do computations over loop counters,including   // accesses to //multi-dimensional arrays zmm0=mdlcincdecstr(k5,zmm0,zmm2,zmm3,imm)  //increment/decrement loopcounters }

Embodiments provide a method of collapsing multi-nested loops by using amulti-dimensional loop counter and increment instructions. In oneembodiment computation of trip counts of the collapsed loop may beprovided, the loop counter values extracted for use in computation, andthen an increment instruction, as described herein occurs, as seen inTable 19.

TABLE 19 tc_of_collapsed_loop =(iend−istart+1)*(jend−jstart+1)*(kend−kstart+1) for(n=0;n<tc_of_collapsed_loop; n++){ //collapsed loop i=extract(i_position,zmm0) //extract nested loop counters from  //multidimensional loop counter  j=extract(j_position,zmm0) k=extract(k_position,zmm0)  computation(i,j,k,B[k][j])  //docomputations over loop counters, including    //accesses tomultidimensional arrays zmm0=MDLCINC(k5,zmm0,zmm2,zmm3) //incrementmulti- dimensional loop   //counter }

In yet another embodiment, the loop counter instruction may be used inconnection with an update to one or more flags of a status register suchas a flag register. For example an update to a zero flag (ZF) or a carryflag (CF) of a flag register of a processor may occur as follows: if(inc==0) ZF=1; if (inc==1) CF=1. This is applicable to all types ofincrement instructions. If (inc==0) then it means an increment has beendone and the loop has crossed to next iteration of collapsed loopsuccessfully. If (inc==1), that means all loop counters have beenupdated to starting values, but no increment is done, in other words thecollapsed loop is over. Such control can be used for control ofcollapsed loop end. Increment instructions with a flag modification canbe used to collapse loops, as seen in Table 20.

TABLE 20 do{ //collapsed loop  i=extract(i_position,zmm0) //extractnested loop counters from  //multidimensional loop counter j=extract(j_position,zmm0)  k=extract(k_position,zmm0) computation(i,j,k,B[k][j])  //do computations over loop counters,including   // accesses to multidimensional arrays zmm0=MDLCINCFLAG(k5,zmm0,zmm2,zmm3) //increment multi-dimensional//loop counter with flag modification }while(ZF==1) //repeat while thereanything left to increment. Also possible //do{ }until(CF==1) - repeatuntil increment will not happen As an example of flag modificationoperation, if there is a loop: for(k=1;k<=3;k++)  for(j=1;j<=3;j++)  for(i=1;i<=3;i++) and already the loop counter vector (mdlc) is equalto 3:3:3, then after increment MDLCINCFLAG(mdlc) a result mdlc=1:1:1occurs and CF==1 (ZF==1).

The instruction variations described herein may be used together with aninstruction to calculate offsets in multi-dimensional arrays. Use ofsuch combinations may avoid compression/extraction instructions forobtaining each individual counter values to access an array. Insteadthis offset calculation instruction uses the vector of current loopcounters to compute the offset from a starting address of the array.

Exemplary Instruction Formats

Embodiments of the instruction(s) described herein may be embodied indifferent formats. For example, the instruction(s) described herein maybe embodied as a VEX, generic vector friendly, or other format. Detailsof VEX and a generic vector friendly format are discussed below.Additionally, exemplary systems, architectures, and pipelines aredetailed below. Embodiments of the instruction(s) may be executed onsuch systems, architectures, and pipelines, but are not limited to thosedetailed.

VEX Instruction Format

VEX encoding allows instructions to have more than two operands, andallows SIMD vector registers to be longer than 128 bits. The use of aVEX prefix provides for three-operand (or more) syntax. For example,previous two-operand instructions performed operations such as A=A+B,which overwrites a source operand. The use of a VEX prefix enablesoperands to perform nondestructive operations such as A=B+C.

FIG. 6A illustrates an exemplary AVX instruction format including a VEXprefix 602, real opcode field 630, Mod R/M byte 640, SIB byte 650,displacement field 662, and IMM8 672. FIG. 6B illustrates which fieldsfrom FIG. 6A make up a full opcode field 674 and a base operation field642. FIG. 6C illustrates which fields from FIG. 6A make up a registerindex field 644.

VEX Prefix (Bytes 0-2) 602 is encoded in a three-byte form. The firstbyte is the Format Field 640 (VEX Byte 0, bits [7:0]), which contains anexplicit C4 byte value (the unique value used for distinguishing the C4instruction format). The second-third bytes (VEX Bytes 1-2) include anumber of bit fields providing specific capability. Specifically, REXfield 605 (VEX Byte 1, bits [7-5]) consists of a VEX.R bit field (VEXByte 1, bit [7]—R), VEX.X bit field (VEX byte 1, bit [6]—X), and VEX.Bbit field (VEX byte 1, bit[5]—B). Other fields of the instructionsencode the lower three bits of the register indexes as is known in theart (rrr, xxx, and bbb), so that Rrrr, Xxxx, and Bbbb may be formed byadding VEX.R, VEX.X, and VEX.B. Opcode map field 615 (VEX byte 1, bits[4:0]—mmmmm) includes content to encode an implied leading opcode byte.W Field 664 (VEX byte 2, bit [7]—W)—is represented by the notationVEX.W, and provides different functions depending on the instruction.The role of VEX.vvvv 620 (VEX Byte 2, bits [6:3]—vvvv) may include thefollowing: 1) VEX.vvvv encodes the first source register operand,specified in inverted (1s complement) form and is valid for instructionswith 2 or more source operands; 2) VEX.vvvv encodes the destinationregister operand, specified in is complement form for certain vectorshifts; or 3) VEX.vvvv does not encode any operand, the field isreserved and should contain 1111b. If VEX.L 668 Size field (VEX byte 2,bit [2]—L)=0, it indicates 128 bit vector; if VEX.L=1, it indicates 256bit vector. Prefix encoding field 625 (VEX byte 2, bits [1:0]—pp)provides additional bits for the base operation field.

Real Opcode Field 630 (Byte 3) is also known as the opcode byte. Part ofthe opcode is specified in this field.

MOD R/M Field 640 (Byte 4) includes MOD field 642 (bits [7-6]), Regfield 644 (bits [5-3]), and R/M field 646 (bits [2-0]). The role of Regfield 644 may include the following: encoding either the destinationregister operand or a source register operand (the rrr of Rrrr), or betreated as an opcode extension and not used to encode any instructionoperand. The role of R/M field 646 may include the following: encodingthe instruction operand that references a memory address, or encodingeither the destination register operand or a source register operand.

Scale, Index, Base (SIB)—The content of Scale field 650 (Byte 5)includes SS652 (bits [7-6]), which is used for memory addressgeneration. The contents of SIB.xxx 654 (bits [5-3]) and SIB.bbb 656(bits [2-0]) have been previously referred to with regard to theregister indexes Xxxx and Bbbb.

The Displacement Field 662 and the immediate field (IMM8) 672 containaddress data.

Generic Vector Friendly Instruction Format

A vector friendly instruction format is an instruction format that issuited for vector instructions (e.g., there are certain fields specificto vector operations). While embodiments are described in which bothvector and scalar operations are supported through the vector friendlyinstruction format, alternative embodiments use only vector operationsthe vector friendly instruction format.

FIGS. 7A-7B are block diagrams illustrating a generic vector friendlyinstruction format and instruction templates thereof according toembodiments of the invention. FIG. 7A is a block diagram illustrating ageneric vector friendly instruction format and class A instructiontemplates thereof according to embodiments of the invention; while FIG.7B is a block diagram illustrating the generic vector friendlyinstruction format and class B instruction templates thereof accordingto embodiments of the invention. Specifically, a generic vector friendlyinstruction format 700 for which are defined class A and class Binstruction templates, both of which include no memory access 705instruction templates and memory access 720 instruction templates. Theterm generic in the context of the vector friendly instruction formatrefers to the instruction format not being tied to any specificinstruction set.

While embodiments of the invention will be described in which the vectorfriendly instruction format supports the following: a 64 byte vectoroperand length (or size) with 32 bit (4 byte) or 64 bit (8 byte) dataelement widths (or sizes) (and thus, a 64 byte vector consists of either16 doubleword-size elements or alternatively, 8 quadword-size elements);a 64 byte vector operand length (or size) with 16 bit (2 byte) or 8 bit(1 byte) data element widths (or sizes); a 32 byte vector operand length(or size) with 32 bit (4 byte), 64 bit (8 byte), 16 bit (2 byte), or 8bit (1 byte) data element widths (or sizes); and a 16 byte vectoroperand length (or size) with 32 bit (4 byte), 64 bit (8 byte), 16 bit(2 byte), or 8 bit (1 byte) data element widths (or sizes); alternativeembodiments may support more, less and/or different vector operand sizes(e.g., 256 byte vector operands) with more, less, or different dataelement widths (e.g., 128 bit (16 byte) data element widths).

The class A instruction templates in FIG. 7A include: 1) within the nomemory access 705 instruction templates there is shown a no memoryaccess, full round control type operation 710 instruction template and ano memory access, data transform type operation 715 instructiontemplate; and 2) within the memory access 720 instruction templatesthere is shown a memory access, temporal 725 instruction template and amemory access, non-temporal 730 instruction template. The class Binstruction templates in FIG. 7B include: 1) within the no memory access705 instruction templates there is shown a no memory access, write maskcontrol, partial round control type operation 712 instruction templateand a no memory access, write mask control, vsize type operation 717instruction template; and 2) within the memory access 720 instructiontemplates there is shown a memory access, write mask control 727instruction template.

The generic vector friendly instruction format 700 includes thefollowing fields listed below in the order illustrated in FIGS. 7A-7B.In conjunction with the discussions above, in an embodiment, referringto the format details provided below in FIGS. 7A-B and 8, either a nonmemory access instruction type 705 or a memory access instruction type720 may be utilized. Addresses for the input vector operand(s) anddestination may be identified in register address field 744 describedbelow. The optional embodiment discussed above also includes a scalarinput which may also be specified in address field 744.

Format field 740—a specific value (an instruction format identifiervalue) in this field uniquely identifies the vector friendly instructionformat, and thus occurrences of instructions in the vector friendlyinstruction format in instruction streams. As such, this field isoptional in the sense that it is not needed for an instruction set thathas only the generic vector friendly instruction format.

Base operation field 742—its content distinguishes different baseoperations.

Register index field 744—its content, directly or through addressgeneration, specifies the locations of the source and destinationoperands, be they in registers or in memory. These include a sufficientnumber of bits to select N registers from a P×Q (e.g. 32×512, 16×128,32×1024, 64×1024) register file. While in one embodiment N may be up tothree sources and one destination register, alternative embodiments maysupport more or less sources and destination registers (e.g., maysupport up to two sources where one of these sources also acts as thedestination, may support up to three sources where one of these sourcesalso acts as the destination, may support up to two sources and onedestination).

Modifier field 746—its content distinguishes occurrences of instructionsin the generic vector instruction format that specify memory access fromthose that do not; that is, between no memory access 705 instructiontemplates and memory access 720 instruction templates. Memory accessoperations read and/or write to the memory hierarchy (in some casesspecifying the source and/or destination addresses using values inregisters), while non-memory access operations do not (e.g., the sourceand destinations are registers). While in one embodiment this field alsoselects between three different ways to perform memory addresscalculations, alternative embodiments may support more, less, ordifferent ways to perform memory address calculations.

Augmentation operation field 750—its content distinguishes which one ofa variety of different operations to be performed in addition to thebase operation. This field is context specific. In one embodiment of theinvention, this field is divided into a class field 768, an alpha field752, and a beta field 754. The augmentation operation field 750 allowscommon groups of operations to be performed in a single instructionrather than 2, 3, or 4 instructions.

Scale field 760—its content allows for the scaling of the index field'scontent for memory address generation (e.g., for address generation thatuses 2scale*index+base).

Displacement Field 762A—its content is used as part of memory addressgeneration (e.g., for address generation that uses2scale*index+base+displacement).

Displacement Factor Field 762B (note that the juxtaposition ofdisplacement field 762A directly over displacement factor field 762Bindicates one or the other is used)—its content is used as part ofaddress generation; it specifies a displacement factor that is to bescaled by the size of a memory access (N)—where N is the number of bytesin the memory access (e.g., for address generation that uses2scale*index+base+scaled displacement). Redundant low-order bits areignored and hence, the displacement factor field's content is multipliedby the memory operands total size (N) in order to generate the finaldisplacement to be used in calculating an effective address. The valueof N is determined by the processor hardware at runtime based on thefull opcode field 774 (described later herein) and the data manipulationfield 754C. The displacement field 762A and the displacement factorfield 762B are optional in the sense that they are not used for the nomemory access 705 instruction templates and/or different embodiments mayimplement only one or none of the two.

Data element width field 764—its content distinguishes which one of anumber of data element widths is to be used (in some embodiments for allinstructions; in other embodiments for only some of the instructions).This field is optional in the sense that it is not needed if only onedata element width is supported and/or data element widths are supportedusing some aspect of the opcodes.

Write mask field 770—its content controls, on a per data elementposition basis, whether that data element position in the destinationvector operand reflects the result of the base operation andaugmentation operation. Class A instruction templates supportmerging-writemasking, while class B instruction templates support bothmerging- and zeroing-writemasking. When merging, vector masks allow anyset of elements in the destination to be protected from updates duringthe execution of any operation (specified by the base operation and theaugmentation operation); in other one embodiment, preserving the oldvalue of each element of the destination where the corresponding maskbit has a 0. In contrast, when zeroing vector masks allow any set ofelements in the destination to be zeroed during the execution of anyoperation (specified by the base operation and the augmentationoperation); in one embodiment, an element of the destination is set to 0when the corresponding mask bit has a 0 value. A subset of thisfunctionality is the ability to control the vector length of theoperation being performed (that is, the span of elements being modified,from the first to the last one); however, it is not necessary that theelements that are modified be consecutive. Thus, the write mask field770 allows for partial vector operations, including loads, stores,arithmetic, logical, etc. While embodiments of the invention aredescribed in which the write mask field's 770 content selects one of anumber of write mask registers that contains the write mask to be used(and thus the write mask field's 770 content indirectly identifies thatmasking to be performed), alternative embodiments instead or additionalallow the mask write field's 770 content to directly specify the maskingto be performed.

Immediate field 772—its content allows for the specification of animmediate. This field is optional in the sense that is it not present inan implementation of the generic vector friendly format that does notsupport immediate and it is not present in instructions that do not usean immediate.

Class field 768—its content distinguishes between different classes ofinstructions. With reference to FIGS. 7A-B, the contents of this fieldselect between class A and class B instructions. In FIGS. 7A-B, roundedcorner squares are used to indicate a specific value is present in afield (e.g., class A 768A and class B 768B for the class field 768respectively in FIGS. 7A-B).

Instruction Templates of Class A

In the case of the non-memory access 705 instruction templates of classA, the alpha field 752 is interpreted as an RS field 752A, whose contentdistinguishes which one of the different augmentation operation typesare to be performed (e.g., round 752A.1 and data transform 752A.2 arerespectively specified for the no memory access, round type operation710 and the no memory access, data transform type operation 715instruction templates), while the beta field 754 distinguishes which ofthe operations of the specified type is to be performed. In the nomemory access 705 instruction templates, the scale field 760, thedisplacement field 762A, and the displacement scale filed 762B are notpresent.

No-Memory Access Instruction Templates—Full Round Control Type Operation

In the no memory access full round control type operation 710instruction template, the beta field 754 is interpreted as a roundcontrol field 754A, whose content(s) provide static rounding. While inthe described embodiments of the invention the round control field 754Aincludes a suppress all floating point exceptions (SAE) field 756 and around operation control field 758, alternative embodiments may supportmay encode both these concepts into the same field or only have one orthe other of these concepts/fields (e.g., may have only the roundoperation control field 758).

SAE field 756—its content distinguishes whether or not to disable theexception event reporting; when the SAE field's 756 content indicatessuppression is enabled, a given instruction does not report any kind offloating-point exception flag and does not raise any floating pointexception handler.

Round operation control field 758—its content distinguishes which one ofa group of rounding operations to perform (e.g., Round-up, Round-down,Round-towards-zero and Round-to-nearest). Thus, the round operationcontrol field 758 allows for the changing of the rounding mode on a perinstruction basis. In one embodiment of the invention where a processorincludes a control register for specifying rounding modes, the roundoperation control field's 750 content overrides that register value.

No Memory Access Instruction Templates—Data Transform Type Operation

In the no memory access data transform type operation 715 instructiontemplate, the beta field 754 is interpreted as a data transform field754B, whose content distinguishes which one of a number of datatransforms is to be performed (e.g., no data transform, swizzle,broadcast).

In the case of a memory access 720 instruction template of class A, thealpha field 752 is interpreted as an eviction hint field 752B, whosecontent distinguishes which one of the eviction hints is to be used (inFIG. 7A, temporal 752B.1 and non-temporal 752B.2 are respectivelyspecified for the memory access, temporal 725 instruction template andthe memory access, non-temporal 730 instruction template), while thebeta field 754 is interpreted as a data manipulation field 754C, whosecontent distinguishes which one of a number of data manipulationoperations (also known as primitives) is to be performed (e.g., nomanipulation; broadcast; up conversion of a source; and down conversionof a destination). The memory access 720 instruction templates includethe scale field 760, and optionally the displacement field 762A or thedisplacement scale field 762B.

Vector memory instructions perform vector loads from and vector storesto memory, with conversion support. As with regular vector instructions,vector memory instructions transfer data from/to memory in a dataelement-wise fashion, with the elements that are actually transferred isdictated by the contents of the vector mask that is selected as thewrite mask.

Memory Access Instruction Templates—Temporal

Temporal data is data likely to be reused soon enough to benefit fromcaching. This is, however, a hint, and different processors mayimplement it in different ways, including ignoring the hint entirely.

Memory Access Instruction Templates—Non-Temporal

Non-temporal data is data unlikely to be reused soon enough to benefitfrom caching in the 1st-level cache and should be given priority foreviction. This is, however, a hint, and different processors mayimplement it in different ways, including ignoring the hint entirely.

Instruction Templates of Class B

In the case of the instruction templates of class B, the alpha field 752is interpreted as a write mask control (Z) field 752C, whose contentdistinguishes whether the write masking controlled by the write maskfield 770 should be a merging or a zeroing.

In the case of the non-memory access 705 instruction templates of classB, part of the beta field 754 is interpreted as an RL field 757A, whosecontent distinguishes which one of the different augmentation operationtypes are to be performed (e.g., round 757A.1 and vector length (VSIZE)757A.2 are respectively specified for the no memory access, write maskcontrol, partial round control type operation 712 instruction templateand the no memory access, write mask control, VSIZE type operation 717instruction template), while the rest of the beta field 754distinguishes which of the operations of the specified type is to beperformed. In the no memory access 705 instruction templates, the scalefield 760, the displacement field 762A, and the displacement scale filed762B are not present.

In the no memory access, write mask control, partial round control typeoperation 710 instruction template, the rest of the beta field 754 isinterpreted as a round operation field 759A and exception eventreporting is disabled (a given instruction does not report any kind offloating-point exception flag and does not raise any floating pointexception handler).

Round operation control field 759A—just as round operation control field758, its content distinguishes which one of a group of roundingoperations to perform (e.g., Round-up, Round-down, Round-towards-zeroand Round-to-nearest). Thus, the round operation control field 759Aallows for the changing of the rounding mode on a per instruction basis.In one embodiment of the invention where a processor includes a controlregister for specifying rounding modes, the round operation controlfield's 750 content overrides that register value.

In the no memory access, write mask control, VSIZE type operation 717instruction template, the rest of the beta field 754 is interpreted as avector length field 759B, whose content distinguishes which one of anumber of data vector lengths is to be performed on (e.g., 128, 256, or512 byte).

In the case of a memory access 720 instruction template of class B, partof the beta field 754 is interpreted as a broadcast field 757B, whosecontent distinguishes whether or not the broadcast type datamanipulation operation is to be performed, while the rest of the betafield 754 is interpreted the vector length field 759B. The memory access720 instruction templates include the scale field 760, and optionallythe displacement field 762A or the displacement scale field 762B.

With regard to the generic vector friendly instruction format 700, afull opcode field 774 is shown including the format field 740, the baseoperation field 742, and the data element width field 764. While oneembodiment is shown where the full opcode field 774 includes all ofthese fields, the full opcode field 774 includes less than all of thesefields in embodiments that do not support all of them. The full opcodefield 774 provides the operation code (opcode).

The augmentation operation field 750, the data element width field 764,and the write mask field 770 allow these features to be specified on aper instruction basis in the generic vector friendly instruction format.

The combination of write mask field and data element width field createtyped instructions in that they allow the mask to be applied based ondifferent data element widths.

The various instruction templates found within class A and class B arebeneficial in different situations. In some embodiments of theinvention, different processors or different cores within a processormay support only class A, only class B, or both classes. For instance, ahigh performance general purpose out-of-order core intended forgeneral-purpose computing may support only class B, a core intendedprimarily for graphics and/or scientific (throughput) computing maysupport only class A, and a core intended for both may support both (ofcourse, a core that has some mix of templates and instructions from bothclasses but not all templates and instructions from both classes iswithin the purview of the invention). Also, a single processor mayinclude multiple cores, all of which support the same class or in whichdifferent cores support different class. For instance, in a processorwith separate graphics and general purpose cores, one of the graphicscores intended primarily for graphics and/or scientific computing maysupport only class A, while one or more of the general purpose cores maybe high performance general purpose cores with out of order executionand register renaming intended for general-purpose computing thatsupport only class B. Another processor that does not have a separategraphics core, may include one more general purpose in-order orout-of-order cores that support both class A and class B. Of course,features from one class may also be implement in the other class indifferent embodiments of the invention. Programs written in a high levellanguage would be put (e.g., just in time compiled or staticallycompiled) into an variety of different executable forms, including: 1) aform having only instructions of the class(es) supported by the targetprocessor for execution; or 2) a form having alternative routineswritten using different combinations of the instructions of all classesand having control flow code that selects the routines to execute basedon the instructions supported by the processor which is currentlyexecuting the code.

Exemplary Specific Vector Friendly Instruction Format

FIG. 8A is a block diagram illustrating an exemplary specific vectorfriendly instruction format according to embodiments of the invention.FIG. 8A shows a specific vector friendly instruction format 800 that isspecific in the sense that it specifies the location, size,interpretation, and order of the fields, as well as values for some ofthose fields. The specific vector friendly instruction format 800 may beused to extend the x86 instruction set, and thus some of the fields aresimilar or the same as those used in the existing x86 instruction setand extension thereof (e.g., AVX). This format remains consistent withthe prefix encoding field, real opcode byte field, MOD R/M field, SIBfield, displacement field, and immediate fields of the existing x86instruction set with extensions. The fields from FIG. 7 into which thefields from FIG. 8A map are illustrated.

It should be understood that, although embodiments of the invention aredescribed with reference to the specific vector friendly instructionformat 800 in the context of the generic vector friendly instructionformat 700 for illustrative purposes, the invention is not limited tothe specific vector friendly instruction format 800 except whereclaimed. For example, the generic vector friendly instruction format 700contemplates a variety of possible sizes for the various fields, whilethe specific vector friendly instruction format 800 is shown as havingfields of specific sizes. By way of specific example, while the dataelement width field 764 is illustrated as a one bit field in thespecific vector friendly instruction format 800, the invention is not solimited (that is, the generic vector friendly instruction format 700contemplates other sizes of the data element width field 764).

The generic vector friendly instruction format 700 includes thefollowing fields listed below in the order illustrated in FIG. 8A.

EVEX Prefix (Bytes 0-3) 802—is encoded in a four-byte form.

Format Field 740 (EVEX Byte 0, bits [7:0])—the first byte (EVEX Byte 0)is the format field 740 and it contains 0x62 (the unique value used fordistinguishing the vector friendly instruction format in one embodimentof the invention).

The second-fourth bytes (EVEX Bytes 1-3) include a number of bit fieldsproviding specific capability.

REX field 805 (EVEX Byte 1, bits [7-5])—consists of a EVEX.R bit field(EVEX Byte 1, bit [7]—R), EVEX.X bit field (EVEX byte 1, bit [6]—X), and757BEX byte 1, bit[5]—B). The EVEX.R, EVEX.X, and EVEX.B bit fieldsprovide the same functionality as the corresponding VEX bit fields, andare encoded using is complement form, i.e. ZMM0 is encoded as 1111B,ZMM15 is encoded as 0000B. Other fields of the instructions encode thelower three bits of the register indexes as is known in the art (rrr,xxx, and bbb), so that Rrrr, Xxxx, and Bbbb may be formed by addingEVEX.R, EVEX.X, and EVEX.B.

REX′ field 710—this is the first part of the REX′ field 710 and is theEVEX.R′ bit field (EVEX Byte 1, bit [4]—R′) that is used to encodeeither the upper 16 or lower 16 of the extended 32 register set. In oneembodiment of the invention, this bit, along with others as indicatedbelow, is stored in bit inverted format to distinguish (in thewell-known x86 32-bit mode) from the BOUND instruction, whose realopcode byte is 62, but does not accept in the MOD R/M field (describedbelow) the value of 11 in the MOD field; alternative embodiments of theinvention do not store this and the other indicated bits below in theinverted format. A value of 1 is used to encode the lower 16 registers.In other words, R′Rrrr is formed by combining EVEX.R′, EVEX.R, and theother RRR from other fields.

Opcode map field 815 (EVEX byte 1, bits [3:0]—mmmm)—its content encodesan implied leading opcode byte (0F, 0F 38, or 0F 3).

Data element width field 764 (EVEX byte 2, bit [7]—W)—is represented bythe notation EVEX.W. EVEX.W is used to define the granularity (size) ofthe datatype (either 32-bit data elements or 64-bit data elements).

EVEX.vvvv 820 (EVEX Byte 2, bits [6:3]—vvvv)—the role of EVEX.vvvv mayinclude the following: 1) EVEX.vvvv encodes the first source registeroperand, specified in inverted (1s complement) form and is valid forinstructions with 2 or more source operands; 2) EVEX.vvvv encodes thedestination register operand, specified in is complement form forcertain vector shifts; or 3) EVEX.vvvv does not encode any operand, thefield is reserved and should contain 1111b. Thus, EVEX.vvvv field 820encodes the 4 low-order bits of the first source register specifierstored in inverted (1s complement) form. Depending on the instruction,an extra different EVEX bit field is used to extend the specifier sizeto 32 registers.

EVEX.U 768 Class field (EVEX byte 2, bit [2]—U)—If EVEX.U=0, itindicates class A or EVEX.U0; if EVEX.U=1, it indicates class B orEVEX.U1.

Prefix encoding field 825 (EVEX byte 2, bits [1:0]—pp)—providesadditional bits for the base operation field. In addition to providingsupport for the legacy SSE instructions in the EVEX prefix format, thisalso has the benefit of compacting the SIMD prefix (rather thanrequiring a byte to express the SIMD prefix, the EVEX prefix requiresonly 2 bits). In one embodiment, to support legacy SSE instructions thatuse a SIMD prefix (66H, F2H, F3H) in both the legacy format and in theEVEX prefix format, these legacy SIMD prefixes are encoded into the SIMDprefix encoding field; and at runtime are expanded into the legacy SIMDprefix prior to being provided to the decoder's PLA (so the PLA canexecute both the legacy and EVEX format of these legacy instructionswithout modification). Although newer instructions could use the EVEXprefix encoding field's content directly as an opcode extension, certainembodiments expand in a similar fashion for consistency but allow fordifferent meanings to be specified by these legacy SIMD prefixes. Analternative embodiment may redesign the PLA to support the 2 bit SIMDprefix encodings, and thus not require the expansion.

Alpha field 752 (EVEX byte 3, bit [7]—EH; also known as EVEX.EH,EVEX.rs, EVEX.RL, EVEX.write mask control, and EVEX.N; also illustratedwith α)—as previously described, this field is context specific.

Beta field 754 (EVEX byte 3, bits [6:4]—SSS, also known as EVEX.s2-0,EVEX.r2-0, EVEX.rr1, EVEX.LL0, EVEX.LLB; also illustrated with βββ)—aspreviously described, this field is context specific.

REX′ field 710—this is the remainder of the REX′ field and is theEVEX.V′ bit field (EVEX Byte 3, bit [3]—V′) that may be used to encodeeither the upper 16 or lower 16 of the extended 32 register set. Thisbit is stored in bit inverted format. A value of 1 is used to encode thelower 16 registers. In other words, V′VVVV is formed by combiningEVEX.V′, EVEX.vvvv.

Write mask field 770 (EVEX byte 3, bits [2:0]—kkk)—its content specifiesthe index of a register in the write mask registers as previouslydescribed. In one embodiment of the invention, the specific valueEVEX.kkk=000 has a special behavior implying no write mask is used forthe particular instruction (this may be implemented in a variety of waysincluding the use of a write mask hardwired to all ones or hardware thatbypasses the masking hardware).

Real Opcode Field 830 (Byte 4) is also known as the opcode byte. Part ofthe opcode is specified in this field.

MOD R/M Field 840 (Byte 5) includes MOD field 842, Reg field 844, andR/M field 846. As previously described, the MOD field's 842 contentdistinguishes between memory access and non-memory access operations.The role of Reg field 844 can be summarized to two situations: encodingeither the destination register operand or a source register operand, orbe treated as an opcode extension and not used to encode any instructionoperand. The role of R/M field 846 may include the following: encodingthe instruction operand that references a memory address, or encodingeither the destination register operand or a source register operand.

Scale, Index, Base (SIB) Byte (Byte 6)—As previously described, thescale field's 750 content is used for memory address generation. SIB.xxx854 and SIB.bbb 856—the contents of these fields have been previouslyreferred to with regard to the register indexes Xxxx and Bbbb.

Displacement field 762A (Bytes 7-10)—when MOD field 842 contains 10,bytes 7-10 are the displacement field 762A, and it works the same as thelegacy 32-bit displacement (disp32) and works at byte granularity.

Displacement factor field 762B (Byte 7)—when MOD field 842 contains 01,byte 7 is the displacement factor field 762B. The location of this fieldis that same as that of the legacy x86 instruction set 8-bitdisplacement (disp8), which works at byte granularity. Since disp8 issign extended, it can only address between −128 and 127 bytes offsets;in terms of 64 byte cache lines, disp8 uses 8 bits that can be set toonly four really useful values −128, −64, 0, and 64; since a greaterrange is often needed, disp32 is used; however, disp32 requires 4 bytes.In contrast to disp8 and disp32, the displacement factor field 762B is areinterpretation of disp8; when using displacement factor field 762B,the actual displacement is determined by the content of the displacementfactor field multiplied by the size of the memory operand access (N).This type of displacement is referred to as disp8*N. This reduces theaverage instruction length (a single byte of used for the displacementbut with a much greater range). Such compressed displacement is based onthe assumption that the effective displacement is multiple of thegranularity of the memory access, and hence, the redundant low-orderbits of the address offset do not need to be encoded. In other words,the displacement factor field 762B substitutes the legacy x86instruction set 8-bit displacement. Thus, the displacement factor field762B is encoded the same way as an x86 instruction set 8-bitdisplacement (so no changes in the Mod RM/SIB encoding rules) with theonly exception that disp8 is overloaded to disp8*N. In other words,there are no changes in the encoding rules or encoding lengths but onlyin the interpretation of the displacement value by hardware (which needsto scale the displacement by the size of the memory operand to obtain abyte-wise address offset).

Immediate field 772 operates as previously described.

Full Opcode Field

FIG. 8B is a block diagram illustrating the fields of the specificvector friendly instruction format 800 that make up the full opcodefield 774 according to one embodiment of the invention. Specifically,the full opcode field 774 includes the format field 740, the baseoperation field 742, and the data element width (W) field 764. The baseoperation field 742 includes the prefix encoding field 825, the opcodemap field 815, and the real opcode field 830.

Register Index Field

FIG. 8C is a block diagram illustrating the fields of the specificvector friendly instruction format 800 that make up the register indexfield 744 according to one embodiment of the invention. Specifically,the register index field 744 includes the REX field 805, the REX′ field810, the MOD R/M.reg field 844, the MOD R/M.r/m field 846, the VVVVfield 820, xxx field 854, and the bbb field 856.

Augmentation Operation Field

FIG. 8D is a block diagram illustrating the fields of the specificvector friendly instruction format 800 that make up the augmentationoperation field 750 according to one embodiment of the invention. Whenthe class (U) field 768 contains 0, it signifies EVEX.U0 (class A 768A);when it contains 1, it signifies EVEX.U1 (class B 768B). When U=0 andthe MOD field 842 contains 11 (signifying a no memory access operation),the alpha field 752 (EVEX byte 3, bit [7]—EH) is interpreted as the rsfield 752A. When the rs field 752A contains a 1 (round 752A.1), the betafield 754 (EVEX byte 3, bits [6:4]—SSS) is interpreted as the roundcontrol field 754A. The round control field 754A includes a one bit SAEfield 756 and a two bit round operation field 758. When the rs field752A contains a 0 (data transform 752A.2), the beta field 754 (EVEX byte3, bits [6:4]—SSS) is interpreted as a three bit data transform field754B. When U=0 and the MOD field 842 contains 00, 01, or 10 (signifyinga memory access operation), the alpha field 752 (EVEX byte 3, bit[7]—EH) is interpreted as the eviction hint (EH) field 752B and the betafield 754 (EVEX byte 3, bits [6:4]—SSS) is interpreted as a three bitdata manipulation field 754C.

When U=1, the alpha field 752 (EVEX byte 3, bit [7]—EH) is interpretedas the write mask control (Z) field 752C. When U=1 and the MOD field 842contains 11 (signifying a no memory access operation), part of the betafield 754 (EVEX byte 3, bit [4]—S0) is interpreted as the RL field 757A;when it contains a 1 (round 757A.1) the rest of the beta field 754 (EVEXbyte 3, bit [6-5]—S2-1) is interpreted as the round operation field759A, while when the RL field 757A contains a 0 (VSIZE 757.A2) the restof the beta field 754 (EVEX byte 3, bit [6-5]—S2-1) is interpreted asthe vector length field 759B (EVEX byte 3, bit [6-5]—L1-0). When U=1 andthe MOD field 842 contains 00, 01, or 10 (signifying a memory accessoperation), the beta field 754 (EVEX byte 3, bits [6:4]—SSS) isinterpreted as the vector length field 759B (EVEX byte 3, bit[6-5]—L1-0) and the broadcast field 757B (EVEX byte 3, bit [4]—B).

Exemplary Register Architecture

FIG. 9 is a block diagram of a register architecture 900 according toone embodiment of the invention. In the embodiment illustrated, thereare 32 vector registers 910 that are 512 bits wide; these registers arereferenced as zmm0 through zmm31. The lower order 256 bits of the lower16 zmm registers are overlaid on registers ymm0-16. The lower order 128bits of the lower 16 zmm registers (the lower order 128 bits of the ymmregisters) are overlaid on registers xmm0-15. The specific vectorfriendly instruction format 800 operates on these overlaid register fileas illustrated in the below tables.

Adjustable Vector Length Class Operations Registers Instruction A (FIG.7A; U = 0) 710, 715, zmm registers (the Templates that do 725, 730vector length is 64 not include the byte) vector length field B (FIG.7B; U = 1) 712 zmm registers (the 759B vector length is 64 byte)Instruction B (FIG. 7B; U = 1) 717, 727 zmm, ymm, or xmm Templates thatdo registers (the vector include the vector length is 64 byte, 32 lengthfield 759B byte, or 16 byte) depending on the vector length field 759B

In other words, the vector length field 759B selects between a maximumlength and one or more other shorter lengths, where each such shorterlength is half the length of the preceding length; and instructionstemplates without the vector length field 759B operate on the maximumvector length. Further, in one embodiment, the class B instructiontemplates of the specific vector friendly instruction format 800 operateon packed or scalar single/double-precision floating point data andpacked or scalar integer data. Scalar operations are operationsperformed on the lowest order data element position in an zmm/ymm/xmmregister; the higher order data element positions are either left thesame as they were prior to the instruction or zeroed depending on theembodiment.

Write mask registers 915—in the embodiment illustrated, there are 8write mask registers (k0 through k7), each 64 bits in size. In analternate embodiment, the write mask registers 915 are 16 bits in size.As previously described, in one embodiment of the invention, the vectormask register k0 cannot be used as a write mask; when the encoding thatwould normally indicate k0 is used for a write mask, it selects ahardwired write mask of 0xFFFF, effectively disabling write masking forthat instruction.

General-purpose registers 925—in the embodiment illustrated, there aresixteen 64-bit general-purpose registers that are used along with theexisting x86 addressing modes to address memory operands. Theseregisters are referenced by the names RAX, RBX, RCX, RDX, RBP, RSI, RDI,RSP, and R8 through R15.

Scalar floating point stack register file (x87 stack) 945, on which isaliased the MMX packed integer flat register file 950—in the embodimentillustrated, the x87 stack is an eight-element stack used to performscalar floating-point operations on 32/64/80-bit floating point datausing the x87 instruction set extension; while the MMX registers areused to perform operations on 64-bit packed integer data, as well as tohold operands for some operations performed between the MMX and XMMregisters.

Alternative embodiments of the invention may use wider or narrowerregisters. Additionally, alternative embodiments of the invention mayuse more, less, or different register files and registers.

Exemplary Core Architectures, Processors, and Computer Architectures

Processor cores may be implemented in different ways, for differentpurposes, and in different processors. For instance, implementations ofsuch cores may include: 1) a general purpose in-order core intended forgeneral-purpose computing; 2) a high performance general purposeout-of-order core intended for general-purpose computing; 3) a specialpurpose core intended primarily for graphics and/or scientific(throughput) computing. Implementations of different processors mayinclude: 1) a CPU including one or more general purpose in-order coresintended for general-purpose computing and/or one or more generalpurpose out-of-order cores intended for general-purpose computing; and2) a coprocessor including one or more special purpose cores intendedprimarily for graphics and/or scientific (throughput). Such differentprocessors lead to different computer system architectures, which mayinclude: 1) the coprocessor on a separate chip from the CPU; 2) thecoprocessor on a separate die in the same package as a CPU; 3) thecoprocessor on the same die as a CPU (in which case, such a coprocessoris sometimes referred to as special purpose logic, such as integratedgraphics and/or scientific (throughput) logic, or as special purposecores); and 4) a system on a chip that may include on the same die thedescribed CPU (sometimes referred to as the application core(s) orapplication processor(s)), the above described coprocessor, andadditional functionality. Exemplary core architectures are describednext, followed by descriptions of exemplary processors and computerarchitectures.

Exemplary Core Architectures In-Order and Out-of-Order Core BlockDiagram

FIG. 10A is a block diagram illustrating both an exemplary in-orderpipeline and an exemplary register renaming, out-of-orderissue/execution pipeline according to embodiments of the invention. FIG.10B is a block diagram illustrating both an exemplary embodiment of anin-order architecture core and an exemplary register renaming,out-of-order issue/execution architecture core to be included in aprocessor according to embodiments of the invention. The solid linedboxes in FIGS. 10A-B illustrate the in-order pipeline and in-order core,while the optional addition of the dashed lined boxes illustrates theregister renaming, out-of-order issue/execution pipeline and core. Giventhat the in-order aspect is a subset of the out-of-order aspect, theout-of-order aspect will be described.

In FIG. 10A, a processor pipeline 1000 includes a fetch stage 1002, alength decode stage 1004, a decode stage 1006, an allocation stage 1008,a renaming stage 1010, a scheduling (also known as a dispatch or issue)stage 1012, a register read/memory read stage 1014, an execute stage1016, a write back/memory write stage 1018, an exception handling stage1022, and a commit stage 1024.

FIG. 10B shows processor core 1090 including a front end unit 1030coupled to an execution engine unit 1050, and both are coupled to amemory unit 1070. The core 1090 may be a reduced instruction setcomputing (RISC) core, a complex instruction set computing (CISC) core,a very long instruction word (VLIW) core, or a hybrid or alternativecore type. As yet another option, the core 1090 may be a special-purposecore, such as, for example, a network or communication core, compressionengine, coprocessor core, general purpose computing graphics processingunit (GPGPU) core, graphics core, or the like.

The front end unit 1030 includes a branch prediction unit 1032 coupledto an instruction cache unit 1034, which is coupled to an instructiontranslation lookaside buffer (TLB) 1036, which is coupled to aninstruction fetch unit 1038, which is coupled to a decode unit 1040. Thedecode unit 1040 (or decoder) may decode instructions, and generate asan output one or more micro-operations, micro-code entry points,microinstructions, other instructions, or other control signals, whichare decoded from, or which otherwise reflect, or are derived from, theoriginal instructions. The decode unit 1040 may be implemented usingvarious different mechanisms. Examples of suitable mechanisms include,but are not limited to, look-up tables, hardware implementations,programmable logic arrays (PLAs), microcode read only memories (ROMs),etc. In one embodiment, the core 1090 includes a microcode ROM or othermedium that stores microcode for certain macroinstructions (e.g., indecode unit 1040 or otherwise within the front end unit 1030). Thedecode unit 1040 is coupled to a rename/allocator unit 1052 in theexecution engine unit 1050.

The execution engine unit 1050 includes the rename/allocator unit 1052coupled to a retirement unit 1054 and a set of one or more schedulerunit(s) 1056. The scheduler unit(s) 1056 represents any number ofdifferent schedulers, including reservations stations, centralinstruction window, etc. The scheduler unit(s) 1056 is coupled to thephysical register file(s) unit(s) 1058. Each of the physical registerfile(s) units 1058 represents one or more physical register files,different ones of which store one or more different data types, such asscalar integer, scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point, status (e.g., aninstruction pointer that is the address of the next instruction to beexecuted), etc. In one embodiment, the physical register file(s) unit1058 comprises a vector registers unit, a write mask registers unit, anda scalar registers unit. These register units may provide architecturalvector registers, vector mask registers, and general purpose registers.The physical register file(s) unit(s) 1058 is overlapped by theretirement unit 1054 to illustrate various ways in which registerrenaming and out-of-order execution may be implemented (e.g., using areorder buffer(s) and a retirement register file(s); using a futurefile(s), a history buffer(s), and a retirement register file(s); using aregister maps and a pool of registers; etc.). The retirement unit 1054and the physical register file(s) unit(s) 1058 are coupled to theexecution cluster(s) 1060. The execution cluster(s) 1060 includes a setof one or more execution units 1062 and a set of one or more memoryaccess units 1064. The execution units 1062 may perform variousoperations (e.g., shifts, addition, subtraction, multiplication) and onvarious types of data (e.g., scalar floating point, packed integer,packed floating point, vector integer, vector floating point). Whilesome embodiments may include a number of execution units dedicated tospecific functions or sets of functions, other embodiments may includeonly one execution unit or multiple execution units that all perform allfunctions. The scheduler unit(s) 1056, physical register file(s) unit(s)1058, and execution cluster(s) 1060 are shown as being possibly pluralbecause certain embodiments create separate pipelines for certain typesof data/operations (e.g., a scalar integer pipeline, a scalar floatingpoint/packed integer/packed floating point/vector integer/vectorfloating point pipeline, and/or a memory access pipeline that each havetheir own scheduler unit, physical register file(s) unit, and/orexecution cluster—and in the case of a separate memory access pipeline,certain embodiments are implemented in which only the execution clusterof this pipeline has the memory access unit(s) 1064). It should also beunderstood that where separate pipelines are used, one or more of thesepipelines may be out-of-order issue/execution and the rest in-order.

The set of memory access units 1064 is coupled to the memory unit 1070,which includes a data TLB unit 1072 coupled to a data cache unit 1074coupled to a level 2 (L2) cache unit 1076. In one exemplary embodiment,the memory access units 1064 may include a load unit, a store addressunit, and a store data unit, each of which is coupled to the data TLBunit 1072 in the memory unit 1070. The instruction cache unit 1034 isfurther coupled to a level 2 (L2) cache unit 1076 in the memory unit1070. The L2 cache unit 1076 is coupled to one or more other levels ofcache and eventually to a main memory.

By way of example, the exemplary register renaming, out-of-orderissue/execution core architecture may implement the pipeline 1000 asfollows: 1) the instruction fetch 1038 performs the fetch and lengthdecoding stages 1002 and 1004; 2) the decode unit 1040 performs thedecode stage 1006; 3) the rename/allocator unit 1052 performs theallocation stage 1008 and renaming stage 1010; 4) the scheduler unit(s)1056 performs the schedule stage 1012; 5) the physical register file(s)unit(s) 1058 and the memory unit 1070 perform the register read/memoryread stage 1014; the execution cluster 1060 perform the execute stage1016; 6) the memory unit 1070 and the physical register file(s) unit(s)1058 perform the write back/memory write stage 1018; 7) various unitsmay be involved in the exception handling stage 1022; and 8) theretirement unit 1054 and the physical register file(s) unit(s) 1058perform the commit stage 1024.

The core 1090 may support one or more instructions sets (e.g., the x86instruction set (with some extensions that have been added with newerversions); the MIPS instruction set of MIPS Technologies of Sunnyvale,Calif.; the ARM instruction set (with optional additional extensionssuch as NEON) of ARM Holdings of Sunnyvale, Calif.), including theinstruction(s) described herein. In one embodiment, the core 1090includes logic to support a packed data instruction set extension (e.g.,AVX1, AVX2, and/or some form of the generic vector friendly instructionformat (U=0 and/or U=1) previously described), thereby allowing theoperations used by many multimedia applications to be performed usingpacked data.

It should be understood that the core may support multithreading(executing two or more parallel sets of operations or threads), and maydo so in a variety of ways including time sliced multithreading,simultaneous multithreading (where a single physical core provides alogical core for each of the threads that physical core issimultaneously multithreading), or a combination thereof (e.g., timesliced fetching and decoding and simultaneous multithreading thereaftersuch as in the Intel® Hyperthreading technology).

While register renaming is described in the context of out-of-orderexecution, it should be understood that register renaming may be used inan in-order architecture. While the illustrated embodiment of theprocessor also includes separate instruction and data cache units1034/1074 and a shared L2 cache unit 1076, alternative embodiments mayhave a single internal cache for both instructions and data, such as,for example, a Level 1 (L1) internal cache, or multiple levels ofinternal cache. In some embodiments, the system may include acombination of an internal cache and an external cache that is externalto the core and/or the processor. Alternatively, all of the cache may beexternal to the core and/or the processor.

Specific Exemplary in-Order Core Architecture

FIGS. 11A-B illustrate a block diagram of a more specific exemplaryin-order core architecture, which core would be one of several logicblocks (including other cores of the same type and/or different types)in a chip. The logic blocks communicate through a high-bandwidthinterconnect network (e.g., a ring network) with some fixed functionlogic, memory I/O interfaces, and other necessary I/O logic, dependingon the application.

FIG. 11A is a block diagram of a single processor core, along with itsconnection to the on-die interconnect network 1102 and with its localsubset of the Level 2 (L2) cache 1104, according to embodiments of theinvention. In one embodiment, an instruction decoder 1100 supports thex86 instruction set with a packed data instruction set extension. An L1cache 1106 allows low-latency accesses to cache memory into the scalarand vector units. While in one embodiment (to simplify the design), ascalar unit 1108 and a vector unit 1110 use separate register sets(respectively, scalar registers 1112 and vector registers 1114) and datatransferred between them is written to memory and then read back in froma level 1 (L1) cache 1106, alternative embodiments of the invention mayuse a different approach (e.g., use a single register set or include acommunication path that allow data to be transferred between the tworegister files without being written and read back).

The local subset of the L2 cache 1104 is part of a global L2 cache thatis divided into separate local subsets, one per processor core. Eachprocessor core has a direct access path to its own local subset of theL2 cache 1104. Data read by a processor core is stored in its L2 cachesubset 1104 and can be accessed quickly, in parallel with otherprocessor cores accessing their own local L2 cache subsets. Data writtenby a processor core is stored in its own L2 cache subset 1104 and isflushed from other subsets, if necessary. The ring network ensurescoherency for shared data. The ring network is bi-directional to allowagents such as processor cores, L2 caches and other logic blocks tocommunicate with each other within the chip. Each ring data-path is1012-bits wide per direction.

FIG. 11B is an expanded view of part of the processor core in FIG. 11Aaccording to embodiments of the invention. FIG. 11B includes an L1 datacache 1106A part of the L1 cache 1104, as well as more detail regardingthe vector unit 1110 and the vector registers 1114. Specifically, thevector unit 1110 is a 16-wide vector processing unit (VPU) (see the16-wide ALU 1128), which executes one or more of integer,single-precision float, and double-precision float instructions. The VPUsupports swizzling the register inputs with swizzle unit 1120, numericconversion with numeric convert units 1122A-B, and replication withreplication unit 1124 on the memory input. Write mask registers 1126allow predicating resulting vector writes.

Processor with Integrated Memory Controller and Graphics

FIG. 12 is a block diagram of a processor 1200 that may have more thanone core, may have an integrated memory controller, and may haveintegrated graphics according to embodiments of the invention. The solidlined boxes in FIG. 12 illustrate a processor 1200 with a single core1202A, a system agent 1210, a set of one or more bus controller units1216, while the optional addition of the dashed lined boxes illustratesan alternative processor 1200 with multiple cores 1202A-N, a set of oneor more integrated memory controller unit(s) 1214 in the system agentunit 1210, and special purpose logic 1208.

Thus, different implementations of the processor 1200 may include: 1) aCPU with the special purpose logic 1208 being integrated graphics and/orscientific (throughput) logic (which may include one or more cores), andthe cores 1202A-N being one or more general purpose cores (e.g., generalpurpose in-order cores, general purpose out-of-order cores, acombination of the two); 2) a coprocessor with the cores 1202A-N being alarge number of special purpose cores intended primarily for graphicsand/or scientific (throughput); and 3) a coprocessor with the cores1202A-N being a large number of general purpose in-order cores. Thus,the processor 1200 may be a general-purpose processor, coprocessor orspecial-purpose processor, such as, for example, a network orcommunication processor, compression engine, graphics processor, GPGPU(general purpose graphics processing unit), a high-throughput manyintegrated core (MIC) coprocessor (including 30 or more cores), embeddedprocessor, or the like. The processor may be implemented on one or morechips. The processor 1200 may be a part of and/or may be implemented onone or more substrates using any of a number of process technologies,such as, for example, BiCMOS, CMOS, or NMOS.

The memory hierarchy includes one or more levels of cache within thecores, a set or one or more shared cache units 1206, and external memory(not shown) coupled to the set of integrated memory controller units1214. The set of shared cache units 1206 may include one or moremid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), orother levels of cache, a last level cache (LLC), and/or combinationsthereof. While in one embodiment a ring based interconnect unit 1212interconnects the integrated graphics logic 1208, the set of sharedcache units 1206, and the system agent unit 1210/integrated memorycontroller unit(s) 1214, alternative embodiments may use any number ofwell-known techniques for interconnecting such units. In one embodiment,coherency is maintained between one or more cache units 1206 and cores1202-A-N.

In some embodiments, one or more of the cores 1202A-N are capable ofmulti-threading. The system agent 1210 includes those componentscoordinating and operating cores 1202A-N. The system agent unit 1210 mayinclude for example a power control unit (PCU) and a display unit. ThePCU may be or include logic and components needed for regulating thepower state of the cores 1202A-N and the integrated graphics logic 1208.The display unit is for driving one or more externally connecteddisplays.

The cores 1202A-N may be homogenous or heterogeneous in terms ofarchitecture instruction set; that is, two or more of the cores 1202A-Nmay be capable of execution the same instruction set, while others maybe capable of executing only a subset of that instruction set or adifferent instruction set.

Exemplary Computer Architectures

FIGS. 13-16 are block diagrams of exemplary computer architectures.Other system designs and configurations known in the arts for laptops,desktops, handheld PCs, personal digital assistants, engineeringworkstations, servers, network devices, network hubs, switches, embeddedprocessors, digital signal processors (DSPs), graphics devices, videogame devices, set-top boxes, micro controllers, cell phones, portablemedia players, hand held devices, and various other electronic devices,are also suitable. In general, a huge variety of systems or electronicdevices capable of incorporating a processor and/or other executionlogic as disclosed herein are generally suitable.

Referring now to FIG. 13, shown is a block diagram of a system 1300 inaccordance with one embodiment of the present invention. The system 1300may include one or more processors 1310, 1315, which are coupled to acontroller hub 1320. In one embodiment the controller hub 1320 includesa graphics memory controller hub (GMCH) 1390 and an Input/Output Hub(IOH) 1350 (which may be on separate chips); the GMCH 1390 includesmemory and graphics controllers to which are coupled memory 1340 and acoprocessor 1345; the IOH 1350 is couples input/output (I/O) devices1360 to the GMCH 1390. Alternatively, one or both of the memory andgraphics controllers are integrated within the processor (as describedherein), the memory 1340 and the coprocessor 1345 are coupled directlyto the processor 1310, and the controller hub 1320 in a single chip withthe IOH 1350.

The optional nature of additional processors 1315 is denoted in FIG. 13with broken lines. Each processor 1310, 1315 may include one or more ofthe processing cores described herein and may be some version of theprocessor 1200.

The memory 1340 may be, for example, dynamic random access memory(DRAM), phase change memory (PCM), or a combination of the two. For atleast one embodiment, the controller hub 1320 communicates with theprocessor(s) 1310, 1315 via a multi-drop bus, such as a frontside bus(FSB), point-to-point interface such as QuickPath Interconnect (QPI), orsimilar connection 1395.

In one embodiment, the coprocessor 1345 is a special-purpose processor,such as, for example, a high-throughput MIC processor, a network orcommunication processor, compression engine, graphics processor, GPGPU,embedded processor, or the like. In one embodiment, controller hub 1320may include an integrated graphics accelerator.

There can be a variety of differences between the physical resources1310, 1315 in terms of a spectrum of metrics of merit includingarchitectural, microarchitectural, thermal, power consumptioncharacteristics, and the like.

In one embodiment, the processor 1310 executes instructions that controldata processing operations of a general type. Embedded within theinstructions may be coprocessor instructions. The processor 1310recognizes these coprocessor instructions as being of a type that shouldbe executed by the attached coprocessor 1345. Accordingly, the processor1310 issues these coprocessor instructions (or control signalsrepresenting coprocessor instructions) on a coprocessor bus or otherinterconnect, to coprocessor 1345. Coprocessor(s) 1345 accept andexecute the received coprocessor instructions.

Referring now to FIG. 14, shown is a block diagram of a first morespecific exemplary system 1400 in accordance with an embodiment of thepresent invention. As shown in FIG. 14, multiprocessor system 1400 is apoint-to-point interconnect system, and includes a first processor 1470and a second processor 1480 coupled via a point-to-point interconnect1450. Each of processors 1470 and 1480 may be some version of theprocessor 1200. In one embodiment of the invention, processors 1470 and1480 are respectively processors 1310 and 1315, while coprocessor 1438is coprocessor 1345. In another embodiment, processors 1470 and 1480 arerespectively processor 1310 coprocessor 1345.

Processors 1470 and 1480 are shown including integrated memorycontroller (IMC) units 1472 and 1482, respectively. Processor 1470 alsoincludes as part of its bus controller units point-to-point (P-P)interfaces 1476 and 1478; similarly, second processor 1480 includes P-Pinterfaces 1486 and 1488. Processors 1470, 1480 may exchange informationvia a point-to-point (P-P) interface 1450 using P-P interface circuits1478, 1488. As shown in FIG. 14, IMCs 1472 and 1482 couple theprocessors to respective memories, namely a memory 1432 and a memory1434, which may be portions of main memory locally attached to therespective processors.

Processors 1470, 1480 may each exchange information with a chipset 1490via individual P-P interfaces 1452, 1454 using point to point interfacecircuits 1476, 1494, 1486, 1498. Chipset 1490 may optionally exchangeinformation with the coprocessor 1438 via a high-performance interface1439. In one embodiment, the coprocessor 1438 is a special-purposeprocessor, such as, for example, a high-throughput MIC processor, anetwork or communication processor, compression engine, graphicsprocessor, GPGPU, embedded processor, or the like.

A shared cache (not shown) may be included in either processor oroutside of both processors, yet connected with the processors via P-Pinterconnect, such that either or both processors' local cacheinformation may be stored in the shared cache if a processor is placedinto a low power mode.

Chipset 1490 may be coupled to a first bus 1416 via an interface 1496.In one embodiment, first bus 1416 may be a Peripheral ComponentInterconnect (PCI) bus, or a bus such as a PCI Express bus or anotherthird generation I/O interconnect bus, although the scope of the presentinvention is not so limited.

As shown in FIG. 14, various I/O devices 1414 may be coupled to firstbus 1416, along with a bus bridge 1418 which couples first bus 1416 to asecond bus 1420. In one embodiment, one or more additional processor(s)1415, such as coprocessors, high-throughput MIC processors, GPGPU's,accelerators (such as, e.g., graphics accelerators or digital signalprocessing (DSP) units), field programmable gate arrays, or any otherprocessor, are coupled to first bus 1416. In one embodiment, second bus1420 may be a low pin count (LPC) bus. Various devices may be coupled toa second bus 1420 including, for example, a keyboard and/or mouse 1422,communication devices 1427 and a storage unit 1428 such as a disk driveor other mass storage device which may include instructions/code anddata 1430, in one embodiment. Further, an audio I/O 1424 may be coupledto the second bus 1420. Note that other architectures are possible. Forexample, instead of the point-to-point architecture of FIG. 14, a systemmay implement a multi-drop bus or other such architecture.

Referring now to FIG. 15, shown is a block diagram of a second morespecific exemplary system 1500 in accordance with an embodiment of thepresent invention. Like elements in FIGS. 14 and 15 bear like referencenumerals, and certain aspects of FIG. 14 have been omitted from FIG. 15in order to avoid obscuring other aspects of FIG. 15.

FIG. 15 illustrates that the processors 1470, 1480 may includeintegrated memory and I/O control logic (“CL”) 1472 and 1482,respectively. Thus, the CL 1472, 1482 include integrated memorycontroller units and include I/O control logic. FIG. 15 illustrates thatnot only are the memories 1432, 1434 coupled to the CL 1472, 1482, butalso that I/O devices 1514 are also coupled to the control logic 1472,1482. Legacy I/O devices 1515 are coupled to the chipset 1490.

Referring now to FIG. 16, shown is a block diagram of a SoC 1600 inaccordance with an embodiment of the present invention. Similar elementsin FIG. 12 bear like reference numerals. Also, dashed lined boxes areoptional features on more advanced SoCs. In FIG. 16, an interconnectunit(s) 1602 is coupled to: an application processor 1610 which includesa set of one or more cores 202A-N and shared cache unit(s) 1206; asystem agent unit 1210; a bus controller unit(s) 1216; an integratedmemory controller unit(s) 1214; a set or one or more coprocessors 1620which may include integrated graphics logic, an image processor, anaudio processor, and a video processor; an static random access memory(SRAM) unit 1630; a direct memory access (DMA) unit 1632; and a displayunit 1640 for coupling to one or more external displays. In oneembodiment, the coprocessor(s) 1620 include a special-purpose processor,such as, for example, a network or communication processor, compressionengine, GPGPU, a high-throughput MIC processor, embedded processor, orthe like.

Embodiments of the mechanisms disclosed herein may be implemented inhardware, software, firmware, or a combination of such implementationapproaches. Embodiments of the invention may be implemented as computerprograms or program code executing on programmable systems comprising atleast one processor, a storage system (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device.

Program code, such as code 1430 illustrated in FIG. 14, may be appliedto input instructions to perform the functions described herein andgenerate output information. The output information may be applied toone or more output devices, in known fashion. For purposes of thisapplication, a processing system includes any system that has aprocessor, such as, for example; a digital signal processor (DSP), amicrocontroller, an application specific integrated circuit (ASIC), or amicroprocessor.

The program code may be implemented in a high level procedural or objectoriented programming language to communicate with a processing system.The program code may also be implemented in assembly or machinelanguage, if desired. In fact, the mechanisms described herein are notlimited in scope to any particular programming language. In any case,the language may be a compiled or interpreted language.

One or more aspects of at least one embodiment may be implemented byrepresentative instructions stored on a machine-readable medium whichrepresents various logic within the processor, which when read by amachine causes the machine to fabricate logic to perform the techniquesdescribed herein. Such representations, known as “IP cores” may bestored on a tangible, machine readable medium and supplied to variouscustomers or manufacturing facilities to load into the fabricationmachines that actually make the logic or processor.

Accordingly, embodiments of the invention also include non-transitory,tangible machine-readable media containing instructions or containingdesign data, such as Hardware Description Language (HDL), which definesstructures, circuits, apparatuses, processors and/or system featuresdescribed herein. Such embodiments may also be referred to as programproducts.

Emulation (Including Binary Translation, Code Morphing, Etc.)

In some cases, an instruction converter may be used to convert aninstruction from a source instruction set to a target instruction set.For example, the instruction converter may translate (e.g., using staticbinary translation, dynamic binary translation including dynamiccompilation), morph, emulate, or otherwise convert an instruction to oneor more other instructions to be processed by the core. The instructionconverter may be implemented in software, hardware, firmware, or acombination thereof. The instruction converter may be on processor, offprocessor, or part on and part off processor.

FIG. 17 is a block diagram contrasting the use of a software instructionconverter to convert binary instructions in a source instruction set tobinary instructions in a target instruction set according to embodimentsof the invention. In the illustrated embodiment, the instructionconverter is a software instruction converter, although alternativelythe instruction converter may be implemented in software, firmware,hardware, or various combinations thereof. FIG. 17 shows a program in ahigh level language 1702 may be compiled using an x86 compiler 1704 togenerate x86 binary code 1706 that may be natively executed by aprocessor with at least one x86 instruction set core 1716. The processorwith at least one x86 instruction set core 1716 represents any processorthat can perform substantially the same functions as an Intel processorwith at least one x86 instruction set core by compatibly executing orotherwise processing (1) a substantial portion of the instruction set ofthe Intel x86 instruction set core or (2) object code versions ofapplications or other software targeted to run on an Intel processorwith at least one x86 instruction set core, in order to achievesubstantially the same result as an Intel processor with at least onex86 instruction set core. The x86 compiler 1704 represents a compilerthat is operable to generate x86 binary code 1706 (e.g., object code)that can, with or without additional linkage processing, be executed onthe processor with at least one x86 instruction set core 1716.Similarly, FIG. 17 shows the program in the high level language 1702 maybe compiled using an alternative instruction set compiler 1708 togenerate alternative instruction set binary code 1710 that may benatively executed by a processor without at least one x86 instructionset core 1714 (e.g., a processor with cores that execute the MIPSinstruction set of MIPS Technologies of Sunnyvale, Calif. and/or thatexecute the ARM instruction set of ARM Holdings of Sunnyvale, Calif.).The instruction converter 1712 is used to convert the x86 binary code1706 into code that may be natively executed by the processor without anx86 instruction set core 1714. This converted code is not likely to bethe same as the alternative instruction set binary code 1710 because aninstruction converter capable of this is difficult to make; however, theconverted code will accomplish the general operation and be made up ofinstructions from the alternative instruction set. Thus, the instructionconverter 1712 represents software, firmware, hardware, or a combinationthereof that, through emulation, simulation or any other process, allowsa processor or other electronic device that does not have an x86instruction set processor or core to execute the x86 binary code 1706.

Embodiments may be used in many different types of systems. For example,in one embodiment a communication device can be arranged to perform thevarious methods and techniques described herein. Of course, the scope ofthe present invention is not limited to a communication device, andinstead other embodiments can be directed to other types of apparatusfor processing instructions, or one or more machine readable mediaincluding instructions that in response to being executed on a computingdevice, cause the device to carry out one or more of the methods andtechniques described herein.

Embodiments may be implemented in code and may be stored on anon-transitory storage medium having stored thereon instructions whichcan be used to program a system to perform the instructions. The storagemedium may include, but is not limited to, any type of disk includingfloppy disks, optical disks, solid state drives (SSDs), compact diskread-only memories (CD-ROMs), compact disk rewritables (CD-RWs), andmagneto-optical disks, semiconductor devices such as read-only memories(ROMs), random access memories (RAMs) such as dynamic random accessmemories (DRAMs), static random access memories (SRAMs), erasableprogrammable read-only memories (EPROMs), flash memories, electricallyerasable programmable read-only memories (EEPROMs), magnetic or opticalcards, or any other type of media suitable for storing electronicinstructions.

While the present invention has been described with respect to a limitednumber of embodiments, those skilled in the art will appreciate numerousmodifications and variations therefrom. It is intended that the appendedclaims cover all such modifications and variations as fall within thetrue spirit and scope of this present invention.

What is claimed is:
 1. A processor comprising: at least one core toexecute instructions, the at least one core including a scalar unit anda vector unit, wherein the vector unit is to access a multi-dimensionalloop counter stored in a vector storage of the processor, themulti-dimensional loop counter including a plurality of loop counterseach of a loop of a nested loop formed a plurality of loops.
 2. Theprocessor of claim 1, wherein the vector unit is to determine whether acollapsed loop generated from the nested loop is completed based on themulti-dimensional loop counter.
 3. The processor of claim 2, wherein thevector unit is to execute a multi-dimensional loop counter incrementinstruction to increment one of the plurality of loop counters toidentify that an iteration of the collapsed loop has been completed. 4.The processor of claim 3, wherein the vector unit is to update a firstflag of a flag register of the processor responsive to incrementing theone of the plurality of loop counters.
 5. The processor of claim 4,wherein the vector unit is update a second flag of the flag registerresponsive to completion of the collapsed loop.
 6. The processor ofclaim 5, wherein the vector unit is to execute the multi-dimensionalloop counter increment instruction to update at least one of theplurality of loop counters to a start value.
 7. The processor of claim6, wherein the collapsed loop is completed when each of the plurality ofloop counters is updated to a corresponding start value.
 8. Theprocessor of claim 2, wherein the scalar unit is to execute a pluralityof iterations of the collapsed loop, the plurality of iterationscorresponding to a product of a trip count of each of the plurality ofloops
 9. The processor of claim 1, wherein a first element of themulti-dimensional loop counter is a loop counter of an innermost loop ofthe plurality of loops, a second element of the multi-dimensional loopcounter is a loop counter of a next innermost loop of the plurality ofloops, and a last element of the multi-dimensional loop counter is aloop counter of an outermost loop of the plurality of loops.
 10. Aprocessor comprising: a decode logic to receive a multi-dimensional loopcounter update instruction and to decode the multi-dimensional loopcounter update instruction into at least one decoded instruction; and anexecution logic to execute the at least one decoded instruction toupdate at least one loop counter value of a first operand associatedwith the multi-dimensional loop counter update instruction by a firstamount.
 11. The processor of claim 10, wherein the first amount isaccording to a value of a second operand associated with themulti-dimensional loop counter update instruction.
 12. The processor ofclaim 10, wherein the execution logic is to update the at least one loopcounter value when a corresponding value of a mask associated with themulti-dimensional loop counter update instruction is of a first state.13. The processor of claim 12, wherein the execution logic is to notupdate a second loop counter value of the first operand when acorresponding value of the mask is of a second state.
 14. The processorof claim 10, wherein the multi-dimensional loop counter updateinstruction is inserted into a code segment by a compiler during a loopcollapse operation.
 15. The processor of claim 14, wherein themulti-dimensional loop counter update instruction is to be executedafter completion of a compute portion of a collapsed loop.
 16. Theprocessor of claim 10, wherein the multi-dimensional loop counter updateinstruction comprises a combined increment and decrement instruction tocause at least one loop counter value of the first operand to beincremented and at least one other loop counter value of the firstoperand to be decremented.
 17. The processor of claim 10, wherein theexecution logic is to update the at least one loop counter value by afirst amount corresponding to a stride value obtained from a secondoperand associated with the multi-dimensional loop counter updateinstruction.
 18. A machine-readable medium having stored thereon aninstruction, which if performed by a machine causes the machine toperform a method comprising: receiving a vector counter updateinstruction, a first vector operand having a plurality of loop counters,a second vector operand, and a mask, in a vector execution unit of aprocessor; determining if a first element of the mask indicates that afirst element of the first vector operand is to be masked; and if thefirst element of the first vector operand is not to be masked, comparingthe first element of the first vector operand to a first element of thesecond vector operand, and updating the first element of the firstvector operand based on the comparison.
 19. The machine-readable mediumof claim 18, wherein the method further comprises incrementing the firstelement of the first vector operand, wherein the instruction comprises avector counter increment instruction.
 20. The machine-readable medium ofclaim 19, wherein the method further comprises incrementing the firstelement of the first vector operand by a first stride value, wherein thevector counter update instruction comprises a vector counter strideincrement instruction.
 21. The machine-readable medium of claim 20,wherein the method further comprises obtaining the first stride valuefrom a first element of a stride vector operand associated with theinstruction.
 22. The machine-readable medium of claim 18, wherein themethod further comprises: incrementing the first element of the firstvector operand; or decrementing a second element of the first vectoroperand, wherein instruction comprises a combined vector counterincrement/decrement instruction.
 23. The machine-readable medium ofclaim 22, wherein the method further comprises determining whether toincrement the first element of the first vector operand based on a firstelement of an immediate value.
 24. The machine-readable medium of claim18, wherein the second vector operand corresponds to a vector of endvalues for the plurality of loop counters of the first vector operand.25. A method comprising: extracting a loop counter value for each of aplurality of loop counters stored in a first vector storage of aprocessor, the plurality of loop counters each associated with one of aplurality of loops of a collapsed loop; performing one or morecomputations in a scalar unit of the processor using a value accessedfrom a multi-dimensional array using at least one of the loop countervalues extracted from the first vector storage; and executing an updateto at least one of the plurality of loop counters stored in the firstvector storage to indicate completion of an iteration of the collapsedloop.
 26. The method of claim 25, further comprising incrementing aniteration count of the collapsed loop, extracting the loop countervalue, performing the one or more computations, and executing the updateuntil the iteration count reaches a trip count.
 27. The method of claim26, wherein the trip count corresponds to a product of a trip count foreach of the plurality of loops.
 28. The method of claim 25, furthercomprising extracting the loop counter value, performing the one or morecomputations, and executing the update until a first flag of a flagregister of the processor equals a first value.